Azure Cognitive Services Health Insights Cancer Profiling client library for .NET

Health Insights is an Azure Applied AI Service built with the Azure Cognitive Services Framework, that leverages multiple Cognitive Services, Healthcare API services and other Azure resources.

TheCancer Profiling model receives clinical records of oncology patients and outputs cancer staging, such as clinical stage TNM categories and pathologic stage TNM categories as well as tumor site, histology.

Source code |Package (NuGet) |API reference documentation |Product documentation

Getting started

Prerequisites

• You need anAzure subscription to use this package.
• An existing Cognitive Services Health Insights instance.

Install the package

Install the Azure Health Insights client Cancer Profiling library for .NET withNuGet:

dotnet add package Azure.Health.Insights.CancerProfiling --prerelease

This table shows the relationship between SDK versions and supported API versions of the service:

Authenticate the client

You can find the endpoint for your Health Insights service resource using theAzure Portal orAzure CLI

# Get the endpoint for the Health Insights service resourceaz cognitiveservices account show --name "resource-name" --resource-group "resource-group-name" --query "properties.endpoint"

Get the API Key

You can get theAPI Key from the Health Insights service resource in the Azure Portal.Alternatively, you can useAzure CLI snippet below to get the API key of your resource.

az cognitiveservices account keys list --resource-group <your-resource-group-name> --name <your-resource-name>

Create CancerProfilingClient with AzureKeyCredential

Once you have the value for the API key, create anAzureKeyCredential. With the endpoint and key credential, you can create theCancerProfilingClient:

string endpoint = "<endpoint>";string apiKey = "<apiKey>";var credential = new AzureKeyCredential(apiKey);var client = new CancerProfilingClient(new Uri(endpoint), credential);

Key concepts

The Cancer Profiling model allows you to infer cancer attributes such as tumor site, histology, clinical stage TNM categories and pathologic stage TNM categories from unstructured clinical documents.

Examples

• Infer Cancer Profiling

Cancer Profiling

OncoPhenotypeResult oncoPhenotypeResult = default;try{    Operation<OncoPhenotypeResult> operation = await client.InferCancerProfileAsync(WaitUntil.Completed, oncoPhenotypeData);    oncoPhenotypeResult = operation.Value;}catch (Exception ex){    Console.WriteLine(ex.ToString());    return;}

// View operation resultsif (oncoPhenotypeResult.Status == JobStatus.Succeeded){    OncoPhenotypeResults oncoResults = oncoPhenotypeResult.Results;    foreach (OncoPhenotypePatientResult patientResult in oncoResults.Patients)    {        Console.WriteLine($"\n==== Inferences of Patient {patientResult.Id} ====");        foreach (OncoPhenotypeInference oncoInference in patientResult.Inferences)        {            Console.WriteLine($"\n=== Clinical Type: {oncoInference.Type.ToString()}  Value: {oncoInference.Value}   ConfidenceScore: {oncoInference.ConfidenceScore} ===");            foreach (InferenceEvidence evidence in oncoInference.Evidence)            {                if (evidence.PatientDataEvidence != null)                {                    var dataEvidence = evidence.PatientDataEvidence;                    Console.WriteLine($"Evidence {dataEvidence.Id} {dataEvidence.Offset} {dataEvidence.Length} {dataEvidence.Text}");                }                if (evidence.PatientInfoEvidence != null)                {                    var infoEvidence = evidence.PatientInfoEvidence;                    Console.WriteLine($"Evidence {infoEvidence.System} {infoEvidence.Code} {infoEvidence.Name} {infoEvidence.Value}");                }            }        }    }}else{    IReadOnlyList<ResponseError> oncoErrors = oncoPhenotypeResult.Errors;    foreach (ResponseError error in oncoErrors)    {        Console.WriteLine($"{error.Code} : {error.Message}");    }}

Troubleshooting

Setting up console logging

The simplest way to see the logs is to enable the console logging.To create an Azure SDK log listener that outputs messages to console use the AzureEventSourceListener.CreateConsoleLogger method.

// Setup a listener to monitor logged events.using AzureEventSourceListener listener = AzureEventSourceListener.CreateConsoleLogger();

To learn more about other logging mechanisms seeDiagnostics Samples.

Next steps

Additional documentation

For more extensive documentation on Azure Health Insights Cancer Profiling, see theCancer Profiling documentation on docs.microsoft.com.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visitcla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted theMicrosoft Open Source Code of Conduct. For more information see theCode of Conduct FAQ or contactopencode@microsoft.com with any additional questions or comments.