Quickstart: Using Text Analytics for health client library and REST API

This article contains Text Analytics for health quickstarts that help with using the supported client libraries, C#, Java, NodeJS, and Python as well as with using the REST API.

Tip

You can use Language Studio to try Language service features without needing to write code.

Reference documentation | Additional samples | Package (NuGet) | Library source code

Use this quickstart to create a Text Analytics for health application with the client library for .NET. In the following example, you will create a C# application that can identify medical entities, relations, and assertions that appear in text.

Prerequisites

  • Azure subscription - Create one for free
  • The Visual Studio IDE
  • Once you have your Azure subscription, create a Language resource in the Azure portal to get your key and endpoint. After it deploys, select Go to resource.
    • You will need the key and endpoint from the resource you create to connect your application to the API. You'll paste your key and endpoint into the code below later in the quickstart.
    • You can use the free pricing tier (Free F0) to try the service (providing 5000 text records - 1000 characters each) and upgrade later to the Standard S pricing tier for production. You can also start with the Standard S pricing tier, receiving the same initial quota for free (5000 text records) before getting charged. For more information on pricing, visit Language Service Pricing.

Setting up

Create environment variables

Your application must be authenticated to send API requests. For production, use a secure way of storing and accessing your credentials. In this example, you will write your credentials to environment variables on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Azure AI services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Language resource key, open a console window, and follow the instructions for your operating system and development environment.

  1. To set the LANGUAGE_KEY environment variable, replace your-key with one of the keys for your resource.
  2. To set the LANGUAGE_ENDPOINT environment variable, replace your-endpoint with the endpoint for your resource.
setx LANGUAGE_KEY your-key
setx LANGUAGE_ENDPOINT your-endpoint

Note

If you only need to access the environment variables in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variables, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

Create a new .NET Core application

Using the Visual Studio IDE, create a new .NET Core console app. This will create a "Hello World" project with a single C# source file: program.cs.

Install the client library by right-clicking on the solution in the Solution Explorer and selecting Manage NuGet Packages. In the package manager that opens select Browse and search for Azure.AI.TextAnalytics. Select version 5.2.0, and then Install. You can also use the Package Manager Console.

Code example

Copy the following code into your program.cs file. Then run the code.

Important

Go to the Azure portal. If the Language resource you created in the Prerequisites section deployed successfully, click the Go to Resource button under Next Steps. You can find your key and endpoint by navigating to your resource's Keys and Endpoint page, under Resource Management.

Important

Remember to remove the key from your code when you're done, and never post it publicly. For production, use a secure way of storing and accessing your credentials like Azure Key Vault. See the Azure AI services security article for more information.

using Azure;
using System;
using Azure.AI.TextAnalytics;
using System.Collections.Generic;
using System.Threading.Tasks;

namespace Example
{
    class Program
    {
        // This example requires environment variables named "LANGUAGE_KEY" and "LANGUAGE_ENDPOINT"
        private static readonly AzureKeyCredential credentials = new (Environment.GetEnvironmentVariable("LANGUAGE_KEY"));
        private static readonly Uri endpoint = new (Environment.GetEnvironmentVariable("LANGUAGE_ENDPOINT"));
        
        // Example method for extracting information from healthcare-related text 
        static async Task healthExample(TextAnalyticsClient client)
        {
            string document = "Prescribed 100mg ibuprofen, taken twice daily.";

            List<string> batchInput = new List<string>()
            {
                document
            };
            AnalyzeHealthcareEntitiesOperation healthOperation = await client.StartAnalyzeHealthcareEntitiesAsync(batchInput);
            await healthOperation.WaitForCompletionAsync();

            await foreach (AnalyzeHealthcareEntitiesResultCollection documentsInPage in healthOperation.Value)
            {
                Console.WriteLine($"Results of Azure Text Analytics for health async model, version: \"{documentsInPage.ModelVersion}\"");
                Console.WriteLine("");

                foreach (AnalyzeHealthcareEntitiesResult entitiesInDoc in documentsInPage)
                {
                    if (!entitiesInDoc.HasError)
                    {
                        foreach (var entity in entitiesInDoc.Entities)
                        {
                            // view recognized healthcare entities
                            Console.WriteLine($"  Entity: {entity.Text}");
                            Console.WriteLine($"  Category: {entity.Category}");
                            Console.WriteLine($"  Offset: {entity.Offset}");
                            Console.WriteLine($"  Length: {entity.Length}");
                            Console.WriteLine($"  NormalizedText: {entity.NormalizedText}");
                        }
                        Console.WriteLine($"  Found {entitiesInDoc.EntityRelations.Count} relations in the current document:");
                        Console.WriteLine("");

                        // view recognized healthcare relations
                        foreach (HealthcareEntityRelation relations in entitiesInDoc.EntityRelations)
                        {
                            Console.WriteLine($"    Relation: {relations.RelationType}");
                            Console.WriteLine($"    For this relation there are {relations.Roles.Count} roles");

                            // view relation roles
                            foreach (HealthcareEntityRelationRole role in relations.Roles)
                            {
                                Console.WriteLine($"      Role Name: {role.Name}");

                                Console.WriteLine($"      Associated Entity Text: {role.Entity.Text}");
                                Console.WriteLine($"      Associated Entity Category: {role.Entity.Category}");
                                Console.WriteLine("");
                            }
                            Console.WriteLine("");
                        }
                    }
                    else
                    {
                        Console.WriteLine("  Error!");
                        Console.WriteLine($"  Document error code: {entitiesInDoc.Error.ErrorCode}.");
                        Console.WriteLine($"  Message: {entitiesInDoc.Error.Message}");
                    }
                    Console.WriteLine("");
                }
            }
        }

        static async Task Main(string[] args)
        {
            var client = new TextAnalyticsClient(endpoint, credentials);
            await healthExample(client);
        }

    }
}

Output

Results of Azure Text Analytics for health async model, version: "2022-03-01"

  Entity: 100mg
  Category: Dosage
  Offset: 11
  Length: 5
  NormalizedText:
  Entity: ibuprofen
  Category: MedicationName
  Offset: 17
  Length: 9
  NormalizedText: ibuprofen
  Entity: twice daily
  Category: Frequency
  Offset: 34
  Length: 11
  NormalizedText:
  Found 2 relations in the current document:

    Relation: DosageOfMedication
    For this relation there are 2 roles
      Role Name: Dosage
      Associated Entity Text: 100mg
      Associated Entity Category: Dosage

      Role Name: Medication
      Associated Entity Text: ibuprofen
      Associated Entity Category: MedicationName


    Relation: FrequencyOfMedication
    For this relation there are 2 roles
      Role Name: Medication
      Associated Entity Text: ibuprofen
      Associated Entity Category: MedicationName

      Role Name: Frequency
      Associated Entity Text: twice daily
      Associated Entity Category: Frequency

Tip

Fast Healthcare Interoperability Resources (FHIR) structuring is available for preview using the Language REST API. The client libraries are not currently supported. Learn more on how to use FHIR structuring in your API call.

Reference documentation | Additional samples | Package (Maven) | Library source code

Use this quickstart to create a Text Analytics for health application with the client library for Java. In the following example, you will create a Java application that can identify medical entities, relations, and assertions that appear in text.

Prerequisites

  • Azure subscription - Create one for free
  • Java Development Kit (JDK) with version 8 or above
  • Once you have your Azure subscription, create a Language resource in the Azure portal to get your key and endpoint. After it deploys, select Go to resource.
    • You will need the key and endpoint from the resource you create to connect your application to the API. You'll paste your key and endpoint into the code below later in the quickstart.
    • You can use the free pricing tier (Free F0) to try the service (providing 5000 text records - 1000 characters each) and upgrade later to the Standard S pricing tier for production. You can also start with the Standard S pricing tier, receiving the same initial quota for free (5000 text records) before getting charged. For more information on pricing, visit Language Service Pricing.

Setting up

Create environment variables

Your application must be authenticated to send API requests. For production, use a secure way of storing and accessing your credentials. In this example, you will write your credentials to environment variables on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Azure AI services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Language resource key, open a console window, and follow the instructions for your operating system and development environment.

  1. To set the LANGUAGE_KEY environment variable, replace your-key with one of the keys for your resource.
  2. To set the LANGUAGE_ENDPOINT environment variable, replace your-endpoint with the endpoint for your resource.
setx LANGUAGE_KEY your-key
setx LANGUAGE_ENDPOINT your-endpoint

Note

If you only need to access the environment variables in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variables, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

Add the client library

Create a Maven project in your preferred IDE or development environment. Then add the following dependency to your project's pom.xml file. You can find the implementation syntax for other build tools online.

<dependencies>
     <dependency>
        <groupId>com.azure</groupId>
        <artifactId>azure-ai-textanalytics</artifactId>
        <version>5.2.0</version>
    </dependency>
</dependencies>

Code example

Create a Java file named EntityLinking.java. Open the file and copy the below code. Then run the code.

Important

Go to the Azure portal. If the Language resource you created in the Prerequisites section deployed successfully, click the Go to Resource button under Next Steps. You can find your key and endpoint by navigating to your resource's Keys and Endpoint page, under Resource Management.

Important

Remember to remove the key from your code when you're done, and never post it publicly. For production, use a secure way of storing and accessing your credentials like Azure Key Vault. See the Azure AI services security article for more information.

import com.azure.core.credential.AzureKeyCredential;
import com.azure.ai.textanalytics.models.*;
import com.azure.ai.textanalytics.TextAnalyticsClientBuilder;
import com.azure.ai.textanalytics.TextAnalyticsClient;

import java.util.List;
import java.util.Arrays;
import com.azure.core.util.Context;
import com.azure.core.util.polling.SyncPoller;

import com.azure.ai.textanalytics.util.*;


public class Example {

    // This example requires environment variables named "LANGUAGE_KEY" and "LANGUAGE_ENDPOINT"
    private static String KEY = System.getenv("LANGUAGE_KEY");
    private static String ENDPOINT = System.getenv("LANGUAGE_ENDPOINT");

    public static void main(String[] args) {
        TextAnalyticsClient client = authenticateClient(languageKey, languageEndpoint);
        healthExample(client);
    }

    // Method to authenticate the client object with your key and endpoint
    static TextAnalyticsClient authenticateClient(String key, String endpoint) {
        return new TextAnalyticsClientBuilder()
                .credential(new AzureKeyCredential(key))
                .endpoint(endpoint)
                .buildClient();
    }

    // Example method for extracting information from healthcare-related text 
    static void healthExample(TextAnalyticsClient client){
        List<TextDocumentInput> documents = Arrays.asList(
                new TextDocumentInput("0",
                        "Prescribed 100mg ibuprofen, taken twice daily."));

        AnalyzeHealthcareEntitiesOptions options = new AnalyzeHealthcareEntitiesOptions().setIncludeStatistics(true);

        SyncPoller<AnalyzeHealthcareEntitiesOperationDetail, AnalyzeHealthcareEntitiesPagedIterable>
                syncPoller = client.beginAnalyzeHealthcareEntities(documents, options, Context.NONE);

        System.out.printf("Poller status: %s.%n", syncPoller.poll().getStatus());
        syncPoller.waitForCompletion();

        // Task operation statistics
        AnalyzeHealthcareEntitiesOperationDetail operationResult = syncPoller.poll().getValue();
        System.out.printf("Operation created time: %s, expiration time: %s.%n",
                operationResult.getCreatedAt(), operationResult.getExpiresAt());
        System.out.printf("Poller status: %s.%n", syncPoller.poll().getStatus());

        for (AnalyzeHealthcareEntitiesResultCollection resultCollection : syncPoller.getFinalResult()) {
            // Model version
            System.out.printf(
                    "Results of Azure Text Analytics for health entities\" Model, version: %s%n",
                    resultCollection.getModelVersion());

            for (AnalyzeHealthcareEntitiesResult healthcareEntitiesResult : resultCollection) {
                System.out.println("Document ID = " + healthcareEntitiesResult.getId());
                System.out.println("Document entities: ");
                // Recognized healthcare entities
                for (HealthcareEntity entity : healthcareEntitiesResult.getEntities()) {
                    System.out.printf(
                            "\tText: %s, normalized name: %s, category: %s, subcategory: %s, confidence score: %f.%n",
                            entity.getText(), entity.getNormalizedText(), entity.getCategory(),
                            entity.getSubcategory(), entity.getConfidenceScore());
                }
                // Recognized healthcare entity relation groups
                for (HealthcareEntityRelation entityRelation : healthcareEntitiesResult.getEntityRelations()) {
                    System.out.printf("Relation type: %s.%n", entityRelation.getRelationType());
                    for (HealthcareEntityRelationRole role : entityRelation.getRoles()) {
                        HealthcareEntity entity = role.getEntity();
                        System.out.printf("\tEntity text: %s, category: %s, role: %s.%n",
                                entity.getText(), entity.getCategory(), role.getName());
                    }
                }
            }
        }
    }
}

Output

Poller status: IN_PROGRESS.
Operation created time: 2022-09-15T19:06:11Z, expiration time: 2022-09-16T19:06:11Z.
Poller status: SUCCESSFULLY_COMPLETED.
Results of Azure Text Analytics for health entities" Model, version: 2022-03-01
Document ID = 0
Document entities: 
	Text: 100mg, normalized name: null, category: Dosage, subcategory: null, confidence score: 0.980000.
	Text: ibuprofen, normalized name: ibuprofen, category: MedicationName, subcategory: null, confidence score: 1.000000.
	Text: twice daily, normalized name: null, category: Frequency, subcategory: null, confidence score: 1.000000.
Relation type: DosageOfMedication.
	Entity text: 100mg, category: Dosage, role: Dosage.
	Entity text: ibuprofen, category: MedicationName, role: Medication.
Relation type: FrequencyOfMedication.
	Entity text: ibuprofen, category: MedicationName, role: Medication.
	Entity text: twice daily, category: Frequency, role: Frequency.

Tip

Fast Healthcare Interoperability Resources (FHIR) structuring is available for preview using the Language REST API. The client libraries are not currently supported. Learn more on how to use FHIR structuring in your API call.

Reference documentation | Additional samples | Package (npm) | Library source code

Use this quickstart to create a Text Analytics for health application with the client library for Node.js. In the following example, you will create a JavaScript application that can identify medical entities, relations, and assertions that appear in text.

Prerequisites

  • Azure subscription - Create one for free
  • Node.js v14 LTS or later
  • Once you have your Azure subscription, create a Language resource in the Azure portal to get your key and endpoint. After it deploys, select Go to resource.
    • You will need the key and endpoint from the resource you create to connect your application to the API. You'll paste your key and endpoint into the code below later in the quickstart.
    • You can use the free pricing tier (Free F0) to try the service (providing 5000 text records - 1000 characters each) and upgrade later to the Standard S pricing tier for production. You can also start with the Standard S pricing tier, receiving the same initial quota for free (5000 text records) before getting charged. For more information on pricing, visit Language Service Pricing.

Setting up

Create environment variables

Your application must be authenticated to send API requests. For production, use a secure way of storing and accessing your credentials. In this example, you will write your credentials to environment variables on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Azure AI services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Language resource key, open a console window, and follow the instructions for your operating system and development environment.

  1. To set the LANGUAGE_KEY environment variable, replace your-key with one of the keys for your resource.
  2. To set the LANGUAGE_ENDPOINT environment variable, replace your-endpoint with the endpoint for your resource.
setx LANGUAGE_KEY your-key
setx LANGUAGE_ENDPOINT your-endpoint

Note

If you only need to access the environment variables in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variables, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

Create a new Node.js application

In a console window (such as cmd, PowerShell, or Bash), create a new directory for your app, and navigate to it.

mkdir myapp 

cd myapp

Run the npm init command to create a node application with a package.json file.

npm init

Install the client library

Install the npm package:

npm install @azure/ai-language-text

Code example

Open the file and copy the below code. Then run the code.

Important

Go to the Azure portal. If the Language resource you created in the Prerequisites section deployed successfully, click the Go to Resource button under Next Steps. You can find your key and endpoint by navigating to your resource's Keys and Endpoint page, under Resource Management.

Important

Remember to remove the key from your code when you're done, and never post it publicly. For production, use a secure way of storing and accessing your credentials like Azure Key Vault. See the Azure AI services security article for more information.

"use strict";

const { TextAnalyticsClient, AzureKeyCredential } = require("@azure/ai-text-analytics");
// This example requires environment variables named "LANGUAGE_KEY" and "LANGUAGE_ENDPOINT"
const key = process.env.LANGUAGE_KEY;
const endpoint = process.env.LANGUAGE_ENDPOINT;

const documents = ["Patient does not suffer from high blood pressure."];
  
  async function main() {
    console.log("== Text analytics for health sample ==");
  
    const client = new TextAnalysisClient(endpoint, new AzureKeyCredential(key));
    const actions = [
      {
        kind: "Healthcare",
      },
    ];
    const poller = await client.beginAnalyzeBatch(actions, documents, "en");
  
    poller.onProgress(() => {
      console.log(
        `Last time the operation was updated was on: ${poller.getOperationState().modifiedOn}`
      );
    });
    console.log(`The operation was created on ${poller.getOperationState().createdOn}`);
    console.log(`The operation results will expire on ${poller.getOperationState().expiresOn}`);
  
    const results = await poller.pollUntilDone();
  
    for await (const actionResult of results) {
      if (actionResult.kind !== "Healthcare") {
        throw new Error(`Expected a healthcare results but got: ${actionResult.kind}`);
      }
      if (actionResult.error) {
        const { code, message } = actionResult.error;
        throw new Error(`Unexpected error (${code}): ${message}`);
      }
      for (const result of actionResult.results) {
        console.log(`- Document ${result.id}`);
        if (result.error) {
          const { code, message } = result.error;
          throw new Error(`Unexpected error (${code}): ${message}`);
        }
        console.log("\tRecognized Entities:");
        for (const entity of result.entities) {
          console.log(`\t- Entity "${entity.text}" of type ${entity.category}`);
          if (entity.dataSources.length > 0) {
            console.log("\t and it can be referenced in the following data sources:");
            for (const ds of entity.dataSources) {
              console.log(`\t\t- ${ds.name} with Entity ID: ${ds.entityId}`);
            }
          }
        }
        if (result.entityRelations.length > 0) {
          console.log(`\tRecognized relations between entities:`);
          for (const relation of result.entityRelations) {
            console.log(
              `\t\t- Relation of type ${relation.relationType} found between the following entities:`
            );
            for (const role of relation.roles) {
              console.log(`\t\t\t- "${role.entity.text}" with the role ${role.name}`);
            }
          }
        }
      }
    }
  }
  
  main().catch((err) => {
    console.error("The sample encountered an error:", err);
  });

Output

== Text analytics for health sample ==
The operation was created on Mon Feb 13 2023 13:12:10 GMT-0800 (Pacific Standard Time)
The operation results will expire on Tue Feb 14 2023 13:12:10 GMT-0800 (Pacific Standard Time)
Last time the operation was updated was on: Mon Feb 13 2023 13:12:10 GMT-0800 (Pacific Standard Time)
- Document 0
    Recognized Entities:
    - Entity "high blood pressure" of type SymptomOrSign
        and it can be referenced in the following data sources:
            - UMLS with Entity ID: C0020538
            - AOD with Entity ID: 0000023317
            - BI with Entity ID: BI00001
            - CCPSS with Entity ID: 1017493
            - CCS with Entity ID: 7.1
            - CHV with Entity ID: 0000015800
            - COSTAR with Entity ID: 397
            - CSP with Entity ID: 0571-5243
            - CST with Entity ID: HYPERTENS
            - DXP with Entity ID: U002034
            - HPO with Entity ID: HP:0000822
            - ICD10 with Entity ID: I10-I15.9
            - ICD10AM with Entity ID: I10-I15.9
            - ICD10CM with Entity ID: I10
            - ICD9CM with Entity ID: 997.91
            - ICPC2ICD10ENG with Entity ID: MTHU035456
            - ICPC2P with Entity ID: K85004
            - LCH with Entity ID: U002317
            - LCH_NW with Entity ID: sh85063723
            - LNC with Entity ID: LA14293-7
            - MDR with Entity ID: 10020772
            - MEDCIN with Entity ID: 33288
            - MEDLINEPLUS with Entity ID: 34
            - MSH with Entity ID: D006973
            - MTH with Entity ID: 005
            - MTHICD9 with Entity ID: 997.91
            - NANDA-I with Entity ID: 00905
            - NCI with Entity ID: C3117
            - NCI_CPTAC with Entity ID: C3117
            - NCI_CTCAE with Entity ID: E13785
            - NCI_CTRP with Entity ID: C3117
            - NCI_FDA with Entity ID: 1908
            - NCI_GDC with Entity ID: C3117
            - NCI_NCI-GLOSS with Entity ID: CDR0000458091
            - NCI_NICHD with Entity ID: C3117
            - NCI_caDSR with Entity ID: C3117
            - NOC with Entity ID: 060808
            - OMIM with Entity ID: MTHU002068
            - PCDS with Entity ID: PRB_11000.06
            - PDQ with Entity ID: CDR0000686951
            - PSY with Entity ID: 23830
            - RCD with Entity ID: XE0Ub
            - SNM with Entity ID: F-70700
            - SNMI with Entity ID: D3-02000
            - SNOMEDCT_US with Entity ID: 38341003
            - WHO with Entity ID: 0210

Tip

Fast Healthcare Interoperability Resources (FHIR) structuring is available for preview using the Language REST API. The client libraries are not currently supported. Learn more on how to use FHIR structuring in your API call.

Reference documentation | Additional samples | Package (PyPi) | Library source code

Use this quickstart to create a Text Analytics for health application with the client library for Python. In the following example, you will create a Python application that can identify medical entities, relations, and assertions that appear in text.

Prerequisites

  • Azure subscription - Create one for free
  • Python 3.8 or later
  • Once you have your Azure subscription, create a Language resource in the Azure portal to get your key and endpoint. After it deploys, select Go to resource.
    • You will need the key and endpoint from the resource you create to connect your application to the API. You'll paste your key and endpoint into the code below later in the quickstart.
    • You can use the free pricing tier (Free F0) to try the service (providing 5000 text records - 1000 characters each) and upgrade later to the Standard S pricing tier for production. You can also start with the Standard S pricing tier, receiving the same initial quota for free (5000 text records) before getting charged. For more information on pricing, visit Language Service Pricing.

Setting up

Create environment variables

Your application must be authenticated to send API requests. For production, use a secure way of storing and accessing your credentials. In this example, you will write your credentials to environment variables on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Azure AI services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Language resource key, open a console window, and follow the instructions for your operating system and development environment.

  1. To set the LANGUAGE_KEY environment variable, replace your-key with one of the keys for your resource.
  2. To set the LANGUAGE_ENDPOINT environment variable, replace your-endpoint with the endpoint for your resource.
setx LANGUAGE_KEY your-key
setx LANGUAGE_ENDPOINT your-endpoint

Note

If you only need to access the environment variables in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variables, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

Install the client library

After installing Python, you can install the client library with:

pip install azure-ai-textanalytics==5.2.0

Code example

Create a new Python file and copy the below code. Then run the code.

Important

Go to the Azure portal. If the Language resource you created in the Prerequisites section deployed successfully, click the Go to Resource button under Next Steps. You can find your key and endpoint by navigating to your resource's Keys and Endpoint page, under Resource Management.

Important

Remember to remove the key from your code when you're done, and never post it publicly. For production, use a secure way of storing and accessing your credentials like Azure Key Vault. See the Azure AI services security article for more information.

# This example requires environment variables named "LANGUAGE_KEY" and "LANGUAGE_ENDPOINT"
key = os.environ.get('LANGUAGE_KEY')
endpoint = os.environ.get('LANGUAGE_ENDPOINT')

from azure.ai.textanalytics import TextAnalyticsClient
from azure.core.credentials import AzureKeyCredential

# Authenticate the client using your key and endpoint 
def authenticate_client():
    ta_credential = AzureKeyCredential(key)
    text_analytics_client = TextAnalyticsClient(
            endpoint=endpoint, 
            credential=ta_credential)
    return text_analytics_client

client = authenticate_client()

# Example function for extracting information from healthcare-related text 
def health_example(client):
    documents = [
        """
        Patient needs to take 50 mg of ibuprofen.
        """
    ]

    poller = client.begin_analyze_healthcare_entities(documents)
    result = poller.result()

    docs = [doc for doc in result if not doc.is_error]

    for idx, doc in enumerate(docs):
        for entity in doc.entities:
            print("Entity: {}".format(entity.text))
            print("...Normalized Text: {}".format(entity.normalized_text))
            print("...Category: {}".format(entity.category))
            print("...Subcategory: {}".format(entity.subcategory))
            print("...Offset: {}".format(entity.offset))
            print("...Confidence score: {}".format(entity.confidence_score))
        for relation in doc.entity_relations:
            print("Relation of type: {} has the following roles".format(relation.relation_type))
            for role in relation.roles:
                print("...Role '{}' with entity '{}'".format(role.name, role.entity.text))
        print("------------------------------------------")
health_example(client)

Output

Entity: 50 mg
...Normalized Text: None
...Category: Dosage
...Subcategory: None
...Offset: 31
...Confidence score: 1.0
Entity: ibuprofen
...Normalized Text: ibuprofen
...Category: MedicationName
...Subcategory: None
...Offset: 40
...Confidence score: 1.0
Relation of type: DosageOfMedication has the following roles
...Role 'Dosage' with entity '50 mg'
...Role 'Medication' with entity 'ibuprofen'

Tip

Fast Healthcare Interoperability Resources (FHIR) structuring is available for preview using the Language REST API. The client libraries are not currently supported. Learn more on how to use FHIR structuring in your API call.

Reference documentation

Use this quickstart to send language detection requests using the REST API. In the following example, you will use cURL to identify medical entities, relations, and assertions that appear in text.

Prerequisites

  • The current version of cURL
  • An Azure subscription - create one for free
  • Once you have your Azure subscription, create a Language resource in the Azure portal to get your key and endpoint. After it deploys, select Go to resource.
    • You will need the key and endpoint from the resource you create to connect your application to the API. You'll paste your key and endpoint into the code below later in the quickstart.
    • You can use the free pricing tier (Free F0) to try the service (providing 5000 text records - 1000 characters each) and upgrade later to the Standard S pricing tier for production. You can also start with the Standard S pricing tier, receiving the same initial quota for free (5000 text records) before getting charged. For more information on pricing, visit Language Service Pricing.

Note

  • The following BASH examples use the \ line continuation character. If your console or terminal uses a different line continuation character, use that character.
  • You can find language specific samples on GitHub.
  • Go to the Azure portal and find the key and endpoint for the Language resource you created in the prerequisites. They will be located on the resource's key and endpoint page, under resource management. Then replace the strings in the code below with your key and endpoint. To call the API, you need the following information:

Setting up

Create environment variables

Your application must be authenticated to send API requests. For production, use a secure way of storing and accessing your credentials. In this example, you will write your credentials to environment variables on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Azure AI services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Language resource key, open a console window, and follow the instructions for your operating system and development environment.

  1. To set the LANGUAGE_KEY environment variable, replace your-key with one of the keys for your resource.
  2. To set the LANGUAGE_ENDPOINT environment variable, replace your-endpoint with the endpoint for your resource.
setx LANGUAGE_KEY your-key
setx LANGUAGE_ENDPOINT your-endpoint

Note

If you only need to access the environment variables in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variables, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

parameter Description
-X POST <endpoint> Specifies your endpoint for accessing the API.
-H Content-Type: application/json The content type for sending JSON data.
-H "Ocp-Apim-Subscription-Key:<key> Specifies the key for accessing the API.
-d <documents> The JSON containing the documents you want to send.

The following cURL commands are executed from a BASH shell. Edit these commands with your own resource name, resource key, and JSON values.

Text Analytics for health

  1. Copy the command into a text editor.
  2. Make the following changes in the command where needed:
    1. Replace the value <your-language-resource-key> with your key.
    2. Replace the first part of the request URL <your-language-resource-endpoint> with your endpoint URL.
  3. Open a command prompt window.
  4. Paste the command from the text editor into the command prompt window, and then run the command.
curl -i -X POST $LANGUAGE_ENDPOINT/language/analyze-text/jobs?api-version=2022-05-15-preview \
-H "Content-Type: application/json" \
-H "Ocp-Apim-Subscription-Key: $LANGUAGE_KEY" \
-d '{"analysisInput":{"documents": [{"text": "The doctor prescried 200mg Ibuprofen.","language": "en","id": "1"}]},"tasks":[{"taskId": "analyze 1","kind": "Healthcare","parameters": {"fhirVersion": "4.0.1"}}]}'

Get the operation-location from the response header. The value will look similar to the following URL:

https://your-resource.cognitiveservices.azure.com/language/analyze-text/jobs/{JOB-ID}?api-version=2022-05-15-preview

To get the results of the request, use the following cURL command. Be sure to replace {JOB-ID} with the numerical ID value you received from the previous operation-location response header:

curl -X GET  $LANGUAGE_ENDPOINT/language/analyze-text/jobs/{JOB-ID}?api-version=2022-05-15-preview \
-H "Content-Type: application/json" \
-H "Ocp-Apim-Subscription-Key: $LANGUAGE_KEY"

JSON response

{
    "jobId": "{JOB-ID}",
    "lastUpdatedDateTime": "2022-06-27T22:04:39Z",
    "createdDateTime": "2022-06-27T22:04:38Z",
    "expirationDateTime": "2022-06-28T22:04:38Z",
    "status": "succeeded",
    "errors": [],
    "tasks": {
        "completed": 1,
        "failed": 0,
        "inProgress": 0,
        "total": 1,
        "items": [
            {
                "kind": "HealthcareLROResults",
                "lastUpdateDateTime": "2022-06-27T22:04:39.7086762Z",
                "status": "succeeded",
                "results": {
                    "documents": [
                        {
                            "id": "1",
                            "entities": [
                                {
                                    "offset": 4,
                                    "length": 6,
                                    "text": "doctor",
                                    "category": "HealthcareProfession",
                                    "confidenceScore": 0.76
                                },
                                {
                                    "offset": 21,
                                    "length": 5,
                                    "text": "200mg",
                                    "category": "Dosage",
                                    "confidenceScore": 0.99
                                },
                                {
                                    "offset": 27,
                                    "length": 9,
                                    "text": "Ibuprofen",
                                    "category": "MedicationName",
                                    "confidenceScore": 1.0,
                                    "name": "ibuprofen",
                                    "links": [
                                        {
                                            "dataSource": "UMLS",
                                            "id": "C0020740"
                                        },
                                        {
                                            "dataSource": "AOD",
                                            "id": "0000019879"
                                        },
                                        {
                                            "dataSource": "ATC",
                                            "id": "M01AE01"
                                        },
                                        {
                                            "dataSource": "CCPSS",
                                            "id": "0046165"
                                        },
                                        {
                                            "dataSource": "CHV",
                                            "id": "0000006519"
                                        },
                                        {
                                            "dataSource": "CSP",
                                            "id": "2270-2077"
                                        },
                                        {
                                            "dataSource": "DRUGBANK",
                                            "id": "DB01050"
                                        },
                                        {
                                            "dataSource": "GS",
                                            "id": "1611"
                                        },
                                        {
                                            "dataSource": "LCH_NW",
                                            "id": "sh97005926"
                                        },
                                        {
                                            "dataSource": "LNC",
                                            "id": "LP16165-0"
                                        },
                                        {
                                            "dataSource": "MEDCIN",
                                            "id": "40458"
                                        },
                                        {
                                            "dataSource": "MMSL",
                                            "id": "d00015"
                                        },
                                        {
                                            "dataSource": "MSH",
                                            "id": "D007052"
                                        },
                                        {
                                            "dataSource": "MTHSPL",
                                            "id": "WK2XYI10QM"
                                        },
                                        {
                                            "dataSource": "NCI",
                                            "id": "C561"
                                        },
                                        {
                                            "dataSource": "NCI_CTRP",
                                            "id": "C561"
                                        },
                                        {
                                            "dataSource": "NCI_DCP",
                                            "id": "00803"
                                        },
                                        {
                                            "dataSource": "NCI_DTP",
                                            "id": "NSC0256857"
                                        },
                                        {
                                            "dataSource": "NCI_FDA",
                                            "id": "WK2XYI10QM"
                                        },
                                        {
                                            "dataSource": "NCI_NCI-GLOSS",
                                            "id": "CDR0000613511"
                                        },
                                        {
                                            "dataSource": "NDDF",
                                            "id": "002377"
                                        },
                                        {
                                            "dataSource": "PDQ",
                                            "id": "CDR0000040475"
                                        },
                                        {
                                            "dataSource": "RCD",
                                            "id": "x02MO"
                                        },
                                        {
                                            "dataSource": "RXNORM",
                                            "id": "5640"
                                        },
                                        {
                                            "dataSource": "SNM",
                                            "id": "E-7772"
                                        },
                                        {
                                            "dataSource": "SNMI",
                                            "id": "C-603C0"
                                        },
                                        {
                                            "dataSource": "SNOMEDCT_US",
                                            "id": "387207008"
                                        },
                                        {
                                            "dataSource": "USP",
                                            "id": "m39860"
                                        },
                                        {
                                            "dataSource": "USPMG",
                                            "id": "MTHU000060"
                                        },
                                        {
                                            "dataSource": "VANDF",
                                            "id": "4017840"
                                        }
                                    ]
                                }
                            ],
                            "relations": [
                                {
                                    "relationType": "DosageOfMedication",
                                    "entities": [
                                        {
                                            "ref": "#/results/documents/0/entities/1",
                                            "role": "Dosage"
                                        },
                                        {
                                            "ref": "#/results/documents/0/entities/2",
                                            "role": "Medication"
                                        }
                                    ]
                                }
                            ],
                            "warnings": [],
                            "fhirBundle": {
                                "resourceType": "Bundle",
                                "id": "95d61191-402a-48c6-9657-a1e4efbda877",
                                "meta": {
                                    "profile": [
                                        "http://hl7.org/fhir/4.0.1/StructureDefinition/Bundle"
                                    ]
                                },
                                "identifier": {
                                    "system": "urn:ietf:rfc:3986",
                                    "value": "urn:uuid:95d61191-402a-48c6-9657-a1e4efbda877"
                                },
                                "type": "document",
                                "entry": [
                                    {
                                        "fullUrl": "Composition/34b666d3-45e7-474d-a398-d3b0329541ad",
                                        "resource": {
                                            "resourceType": "Composition",
                                            "id": "34b666d3-45e7-474d-a398-d3b0329541ad",
                                            "status": "final",
                                            "type": {
                                                "coding": [
                                                    {
                                                        "system": "http://loinc.org",
                                                        "code": "11526-1",
                                                        "display": "Pathology study"
                                                    }
                                                ],
                                                "text": "Pathology study"
                                            },
                                            "subject": {
                                                "reference": "Patient/68dd21ce-58ae-4e59-9445-8331f99899ed",
                                                "type": "Patient"
                                            },
                                            "encounter": {
                                                "reference": "Encounter/90c75fea-4526-4e94-82f8-8df3bc983a14",
                                                "type": "Encounter",
                                                "display": "unknown"
                                            },
                                            "date": "2022-06-27",
                                            "author": [
                                                {
                                                    "reference": "Practitioner/a8ef1526-d4ce-41df-96df-e9d03428c840",
                                                    "type": "Practitioner",
                                                    "display": "Unknown"
                                                }
                                            ],
                                            "title": "Pathology study",
                                            "section": [
                                                {
                                                    "title": "General",
                                                    "code": {
                                                        "coding": [
                                                            {
                                                                "system": "",
                                                                "display": "Unrecognized Section"
                                                            }
                                                        ],
                                                        "text": "General"
                                                    },
                                                    "text": {
                                                        "div": "<div>\r\n\t\t\t\t\t\t\t<h1>General</h1>\r\n\t\t\t\t\t\t\t<p>The doctor prescried 200mg Ibuprofen.</p>\r\n\t\t\t\t\t</div>"
                                                    },
                                                    "entry": [
                                                        {
                                                            "reference": "List/c8ca6757-1d7c-4c49-94e9-ef5263cb943c",
                                                            "type": "List",
                                                            "display": "General"
                                                        }
                                                    ]
                                                }
                                            ]
                                        }
                                    },
                                    {
                                        "fullUrl": "Practitioner/a8ef1526-d4ce-41df-96df-e9d03428c840",
                                        "resource": {
                                            "resourceType": "Practitioner",
                                            "id": "a8ef1526-d4ce-41df-96df-e9d03428c840",
                                            "extension": [
                                                {
                                                    "extension": [
                                                        {
                                                            "url": "offset",
                                                            "valueInteger": -1
                                                        },
                                                        {
                                                            "url": "length",
                                                            "valueInteger": 7
                                                        }
                                                    ],
                                                    "url": "http://hl7.org/fhir/StructureDefinition/derivation-reference"
                                                }
                                            ],
                                            "name": [
                                                {
                                                    "text": "Unknown",
                                                    "family": "Unknown"
                                                }
                                            ]
                                        }
                                    },
                                    {
                                        "fullUrl": "Patient/68dd21ce-58ae-4e59-9445-8331f99899ed",
                                        "resource": {
                                            "resourceType": "Patient",
                                            "id": "68dd21ce-58ae-4e59-9445-8331f99899ed",
                                            "gender": "unknown"
                                        }
                                    },
                                    {
                                        "fullUrl": "Encounter/90c75fea-4526-4e94-82f8-8df3bc983a14",
                                        "resource": {
                                            "resourceType": "Encounter",
                                            "id": "90c75fea-4526-4e94-82f8-8df3bc983a14",
                                            "meta": {
                                                "profile": [
                                                    "http://hl7.org/fhir/us/core/StructureDefinition/us-core-encounter"
                                                ]
                                            },
                                            "status": "finished",
                                            "class": {
                                                "system": "http://terminology.hl7.org/CodeSystem/v3-ActCode",
                                                "display": "unknown"
                                            },
                                            "subject": {
                                                "reference": "Patient/68dd21ce-58ae-4e59-9445-8331f99899ed",
                                                "type": "Patient"
                                            }
                                        }
                                    },
                                    {
                                        "fullUrl": "MedicationStatement/17aeee32-1189-47fc-9223-8abe174f1292",
                                        "resource": {
                                            "resourceType": "MedicationStatement",
                                            "id": "17aeee32-1189-47fc-9223-8abe174f1292",
                                            "extension": [
                                                {
                                                    "extension": [
                                                        {
                                                            "url": "offset",
                                                            "valueInteger": 27
                                                        },
                                                        {
                                                            "url": "length",
                                                            "valueInteger": 9
                                                        }
                                                    ],
                                                    "url": "http://hl7.org/fhir/StructureDefinition/derivation-reference"
                                                }
                                            ],
                                            "status": "active",
                                            "medicationCodeableConcept": {
                                                "coding": [
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls",
                                                        "code": "C0020740",
                                                        "display": "ibuprofen"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/aod",
                                                        "code": "0000019879"
                                                    },
                                                    {
                                                        "system": "http://www.whocc.no/atc",
                                                        "code": "M01AE01"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/ccpss",
                                                        "code": "0046165"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/chv",
                                                        "code": "0000006519"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/csp",
                                                        "code": "2270-2077"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/drugbank",
                                                        "code": "DB01050"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/gs",
                                                        "code": "1611"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/lch_nw",
                                                        "code": "sh97005926"
                                                    },
                                                    {
                                                        "system": "http://loinc.org",
                                                        "code": "LP16165-0"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/medcin",
                                                        "code": "40458"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/mmsl",
                                                        "code": "d00015"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/msh",
                                                        "code": "D007052"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/mthspl",
                                                        "code": "WK2XYI10QM"
                                                    },
                                                    {
                                                        "system": "http://ncimeta.nci.nih.gov",
                                                        "code": "C561"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/nci_ctrp",
                                                        "code": "C561"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/nci_dcp",
                                                        "code": "00803"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/nci_dtp",
                                                        "code": "NSC0256857"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/nci_fda",
                                                        "code": "WK2XYI10QM"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/nci_nci-gloss",
                                                        "code": "CDR0000613511"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/nddf",
                                                        "code": "002377"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/pdq",
                                                        "code": "CDR0000040475"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/rcd",
                                                        "code": "x02MO"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/rxnorm",
                                                        "code": "5640"
                                                    },
                                                    {
                                                        "system": "http://snomed.info/sct",
                                                        "code": "E-7772"
                                                    },
                                                    {
                                                        "system": "http://snomed.info/sct/900000000000207008",
                                                        "code": "C-603C0"
                                                    },
                                                    {
                                                        "system": "http://snomed.info/sct/731000124108",
                                                        "code": "387207008"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/usp",
                                                        "code": "m39860"
                                                    },
                                                    {
                                                        "system": "http://www.nlm.nih.gov/research/umls/uspmg",
                                                        "code": "MTHU000060"
                                                    },
                                                    {
                                                        "system": "http://hl7.org/fhir/ndfrt",
                                                        "code": "4017840"
                                                    }
                                                ],
                                                "text": "Ibuprofen"
                                            },
                                            "subject": {
                                                "reference": "Patient/68dd21ce-58ae-4e59-9445-8331f99899ed",
                                                "type": "Patient"
                                            },
                                            "context": {
                                                "reference": "Encounter/90c75fea-4526-4e94-82f8-8df3bc983a14",
                                                "type": "Encounter",
                                                "display": "unknown"
                                            },
                                            "dosage": [
                                                {
                                                    "text": "200mg",
                                                    "doseAndRate": [
                                                        {
                                                            "doseQuantity": {
                                                                "value": 200
                                                            }
                                                        }
                                                    ]
                                                }
                                            ]
                                        }
                                    },
                                    {
                                        "fullUrl": "List/c8ca6757-1d7c-4c49-94e9-ef5263cb943c",
                                        "resource": {
                                            "resourceType": "List",
                                            "id": "c8ca6757-1d7c-4c49-94e9-ef5263cb943c",
                                            "status": "current",
                                            "mode": "snapshot",
                                            "title": "General",
                                            "subject": {
                                                "reference": "Patient/68dd21ce-58ae-4e59-9445-8331f99899ed",
                                                "type": "Patient"
                                            },
                                            "encounter": {
                                                "reference": "Encounter/90c75fea-4526-4e94-82f8-8df3bc983a14",
                                                "type": "Encounter",
                                                "display": "unknown"
                                            },
                                            "entry": [
                                                {
                                                    "item": {
                                                        "reference": "MedicationStatement/17aeee32-1189-47fc-9223-8abe174f1292",
                                                        "type": "MedicationStatement",
                                                        "display": "Ibuprofen"
                                                    }
                                                }
                                            ]
                                        }
                                    }
                                ]
                            }
                        }
                    ],
                    "errors": [],
                    "modelVersion": "2022-03-01"
                }
            }
        ]
    }
}

Tip

Fast Healthcare Interoperability Resources (FHIR) structuring is available for preview using the Language REST API. The client libraries are not currently supported. Learn more on how to use FHIR structuring in your API call.

Clean up resources

If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.

Next steps