Azure.Health.Insights.ClinicalMatching 1.0.0-beta.1

Azure Cognitive Services Health Insights Clinical Matching 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.

The Clinical Matching model receives patients data and clinical trials protocols, and provides relevant clinical trials based on eligibility criteria.

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

Getting started

Prerequisites

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

Install the package

Install the Azure Health Insights client Clinical Matchinglibrary for .NET with NuGet:

dotnet add package Azure.Health.Insights.ClinicalMatching --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 the Azure Portal or Azure CLI

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

Get the API Key

You can get the API Key from the Health Insights service resource in the Azure Portal. Alternatively, you can use Azure 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 ClinicalMatchingClient with AzureKeyCredential

Once you have the value for the API key, create an AzureKeyCredential. With the endpoint and key credential, you can create the ClinicalMatchingClient:

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

Key concepts

Trial Matcher provides the user of the services two main modes of operation: patients centric and clinical trial centric.

• On patient centric mode, the Trial Matcher model bases the patient matching on the clinical condition, location, priorities, eligibility criteria, and other criteria that the patient and/or service users may choose to prioritize. The model helps narrow down and prioritize the set of relevant clinical trials to a smaller set of trials to start with, that the specific patient appears to be qualified for.
• On clinical trial centric, the Trial Matcher is finding a group of patients potentially eligible to a clinical trial. The Trial Matcher narrows down the patients, first filtered on clinical condition and selected clinical observations, and then focuses on those patients who met the baseline criteria, to find the group of patients that appears to be eligible patients to a trial.

Examples

• Match Trials

Match Trials

TrialMatcherResult trialMatcherResult = default;
try
{
    // Using ClinicalMatchingClient + MatchTrialsAsync
    Operation<TrialMatcherResult> operation = await clinicalMatchingClient.MatchTrialsAsync(WaitUntil.Completed, trialMatcherData);
    trialMatcherResult = operation.Value;
}
catch (Exception ex)
{
    Console.WriteLine(ex.ToString());
    return;
}

// View the match trials (eligible/ineligible)
if (trialMatcherResult.Status == JobStatus.Succeeded)
{
    TrialMatcherResults matcherResults = trialMatcherResult.Results;
    foreach (TrialMatcherPatientResult patientResult in matcherResults.Patients)
    {
        Console.WriteLine($"Inferences of Patient {patientResult.Id}");
        foreach (TrialMatcherInference tmInferences in patientResult.Inferences)
        {
            Console.WriteLine($"Trial Id {tmInferences.Id}");
            Console.WriteLine($"Type: {tmInferences.Type.ToString()}  Value: {tmInferences.Value}");
            Console.WriteLine($"Description {tmInferences.Description}");
        }
    }
}
else
{
    IReadOnlyList<ResponseError> matcherErrors = trialMatcherResult.Errors;
    foreach (ResponseError error in matcherErrors)
    {
        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 see Diagnostics Samples.

Next steps

Additional documentation

For more extensive documentation on Azure Health Insights Clinical Matching, see the Clinical Matching 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, visit cla.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 the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.