Merge pull request #1 from koen-mertens/radiology-insights-GA-cb3

Radiology insights ga cb3

Author: koen-mertens

sdk/healthinsights/azure-healthinsights-radiologyinsights/README.md

@@ -7,7 +7,7 @@
 
 ### Prequisites
 
-- Python 3.8 or later is required to use this package.
+- [Python 3.8+][python] is required to use this package.
 - You need an [Azure subscription][azure_sub] to use this package.
 - An existing Cognitive Services Health Insights instance.
 
@@ -51,7 +51,7 @@ az cognitiveservices account keys list --resource-group <your-resource-group-nam
 Once you have the value for the API key, you can pass it as a string into an instance of **AzureKeyCredential**. Use the key as the credential parameter to authenticate the client:
 
 <!-- SNIPPET:sample_critical_result_inference_async.create_radiology_insights_client-->
-```python 
+```Python 
 import os
 from azure.core.credentials import AzureKeyCredential
 from azure.healthinsights.radiologyinsights import RadiologyInsightsClient
@@ -76,31 +76,154 @@ Sample code snippets are provided to illustrate using long-running operations [b
 
 ## Key concepts
 
+Once you've initialized a 'RadiologyInsightsClient', you can use it to analyse document text by displaying inferences found within the text.
+* Age Mismatch
+* Laterality Discrepancy
+* Sex Mismatch
+* Complete Order Discrepancy
+* Limited Order Discrepancy
+* Finding
+* Critical Result
+* Follow-up Recommendation
+* Communication
+* Radiology Procedure
 Radiology Insights currently supports one document from one patient. Please take a look [here][inferences] for more detailed information about the inferences this service produces. 
 
 ## Examples
 
-### Create a RadiologyInsights request and get the result using an asynchronous client
-
+For each inference samples are available that show how to retrieve the information either in a synchronous (block until operation is complete, slower) or in an asynchronous way (non-blocking, faster).
 For an example how to create a client, a request and get the result see the example in the [sample folder][sample_folder].
 
+* [Age Mismatch](#get-age-mismatch-inference-information)
+* [Complete Order Discrepancy](#get-complete-order-discrepancy-inference-information)
+* [Critical Result](#get-critical-result-inference-information)
+* [Finding](#get-finding-information)
+* [Follow-up Communication](#get-follow-up-communication-information)
+* [Follow-up Recommendation](#get-follow-up-recommendation-information)
+* [Laterality Descripancy](#get-laterality-discrepancy-information)
+* [Limited Order Descripancy](#get-limited-order-discrepancy-information)
+* [Radiology Procedure](#get-radiology-procedure-information)
+* [Sex Mismatch](#get-sex-mismatch-information)
+
+### Running the samples
+
+1. Open a terminal window and `cd` to the directory that the samples are saved in.
+2. Set the environment variables specified in the sample file you wish to run.
+
+### Get Age Mismatch Inference information
+
+<!-- SNIPPET:sample_age_mismatch_inference_async.display_age_mismatch-->
+```Python
+for patient_result in radiology_insights_result.patient_results:
+    for ri_inference in patient_result.inferences:
+        if ri_inference.kind == models.RadiologyInsightsInferenceType.AGE_MISMATCH:
+            print(f"Age Mismatch Inference found")
+```
+<!-- SNIPPET:sample_age_mismatch_inference_async.display_age_mismatch-->
+
+### Get Complete Order Discrepancy Inference information
+
+<!-- SNIPPET:sample_complete_order_discrespancy_inference_async.display_complete_order_discrepancy-->
+```Python
+for patient_result in radiology_insights_result.patient_results:
+            for ri_inference in patient_result.inferences:
+                if ri_inference.kind == models.RadiologyInsightsInferenceType.COMPLETE_ORDER_DISCREPANCY:
+                    print(f"Complete Order Discrepancy Inference found")
+```
+<!-- SNIPPET:sample_complete_order_discrespancy_inference_async.display_complete_order_discrepancy-->
+
 ### Get Critical Result Inference information
 
 <!-- SNIPPET:sample_critical_result_inference_async.display_critical_results-->
-```python
+```Python
 for patient_result in radiology_insights_result.patient_results:
     for ri_inference in patient_result.inferences:
-        if (
-            ri_inference.kind
-            == models.RadiologyInsightsInferenceType.CRITICAL_RESULT
-        ):
+        if ri_inference.kind == models.RadiologyInsightsInferenceType.CRITICAL_RESULT:
             critical_result = ri_inference.result
-            print(
-                f"Critical Result Inference found: {critical_result.description}"
-            )
+                print(
+                f"Critical Result Inference found: {critical_result.description}")
 ```
 <!-- SNIPPET:sample_critical_result_inference_async.display_critical_results-->
 
+### Get Finding Inference information
+
+<!-- SNIPPET:sample_finding_inference_async.display_finding-->
+```Python
+for patient_result in radiology_insights_result.patient_results:
+            counter = 0
+            for ri_inference in patient_result.inferences:
+                if ri_inference.kind == models.RadiologyInsightsInferenceType.FINDING:
+                    counter += 1
+                    print(f"Finding Inference found")
+```
+<!-- SNIPPET:sample_finding_inference_async.display_finding-->
+
+### Get Follow-up Communication information
+
+<!-- SNIPPET:sample_followup_communication_inference_async.display_followup_communication-->
+```Python
+for patient_result in radiology_insights_result.patient_results:
+    for ri_inference in patient_result.inferences:
+        if ri_inference.kind == models.RadiologyInsightsInferenceType.FOLLOWUP_COMMUNICATION:
+            print(f"Follow-up Communication Inference found")
+```
+<!-- SNIPPET:sample_followup_communication_inference_async.display_followup_communication-->
+
+### Get Follow-up Recommendation information
+
+<!-- SNIPPET:sample_followup_recommendation_inference_async.display_followup_recommendation-->
+```Python
+for patient_result in radiology_insights_result.patient_results:
+    for ri_inference in patient_result.inferences:
+        if ri_inference.kind == models.RadiologyInsightsInferenceType.FOLLOWUP_RECOMMENDATION:
+            print(f"Follow-up Recommendation Inference found") 
+```
+<!-- SNIPPET:sample_followup_recommendation_inference_async.display_followup_recommendation-->
+
+### Get Laterality Discrepancy information
+
+<!-- SNIPPET:sample_laterality_discrepancy_inference_async.display_laterality_discrepancy-->
+```Python
+for patient_result in radiology_insights_result.patient_results:
+    for ri_inference in patient_result.inferences:
+        if ri_inference.kind == models.RadiologyInsightsInferenceType.LATERALITY_DISCREPANCY:
+            print(f"Laterality Discrepancy Inference found")
+```
+<!-- SNIPPET:sample_laterality_discrepancy_inference_async.display_laterality_discrepancy-->
+
+### Get Limited Order Discrepancy information
+
+<!-- SNIPPET:sample_limited_order_discrepancy_inference_async.display_limited_order_discrepancy-->
+```Python
+for patient_result in radiology_insights_result.patient_results:
+    for ri_inference in patient_result.inferences:
+        if ri_inference.kind == models.RadiologyInsightsInferenceType.LIMITED_ORDER_DISCREPANCY:
+            print(f"Limited Order Discrepancy Inference found")
+```
+<!-- SNIPPET:sample_limited_order_discrepancy_inference_async.display_limited_order_discrepancy-->
+
+### Get Radiology Procedure information
+
+<!-- SNIPPET:sample_radiology_procedure_inference_async.display_radiology_procedure-->
+```Python
+for patient_result in radiology_insights_result.patient_results:
+    for ri_inference in patient_result.inferences:
+        if ri_inference.kind == models.RadiologyInsightsInferenceType.RADIOLOGY_PROCEDURE:
+            print(f"Radiology Procedure Inference found")
+```
+<!-- SNIPPET:sample_radiology_procedure_inference_async.display_radiology_procedure-->
+
+### Get Sex Mismatch information
+
+<!-- SNIPPET:sample_sex_mismatch_inference_async.display_sex_mismatch-->
+```Python
+for patient_result in radiology_insights_result.patient_results:
+    for ri_inference in patient_result.inferences:
+        if ri_inference.kind == models.RadiologyInsightsInferenceType.SEX_MISMATCH:
+            print(f"Sex Mismatch Inference found")
+```
+<!-- SNIPPET:sample_sex_mismatch_inference_async.display_sex_mismatch-->
+
 For detailed conceptual information of this and other inferences please read more [here][inferences].
 
 ## Troubleshooting
@@ -140,6 +263,8 @@ see the Code of Conduct FAQ or contact <opencode@microsoft.com> with any
 additional questions or comments.
 
 <!-- LINKS -->
+[azure_cli]: https://docs.microsoft.com/cli/azure
+[azure_portal]: https://portal.azure.com
 [health_insights]: https://learn.microsoft.com/azure/azure-health-insights/overview
 [radiology_insights_docs]: https://learn.microsoft.com/azure/azure-health-insights/radiology-insights/
 [azure_sub]: https://azure.microsoft.com/free/
@@ -148,4 +273,5 @@ additional questions or comments.
 [azure_cli]: https://learn.microsoft.com/cli/azure/
 [inferences]: https://learn.microsoft.com/azure/azure-health-insights/radiology-insights/inferences
 [code_of_conduct]: https://opensource.microsoft.com/codeofconduct/
+[python]: https://www.python.org/downloads/
 [sample_folder]: https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/healthinsights/azure-healthinsights-radiologyinsights/samples

sdk/healthinsights/azure-healthinsights-radiologyinsights/azure/healthinsights/radiologyinsights/_client.py

@@ -27,11 +27,10 @@ class RadiologyInsightsClient(
     :param endpoint: Supported Cognitive Services endpoints (protocol and hostname, for example:
      https://westus2.api.cognitive.microsoft.com). Required.
     :type endpoint: str
-    :param credential: Credential needed for the client to connect to Azure. Required.
+    :param credential: Credential used to authenticate requests to the service. Required.
     :type credential: ~azure.core.credentials.AzureKeyCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2023-09-01-preview". Note that overriding this default value may result in unsupported
-     behavior.
+    :keyword api_version: The API version to use for this operation. Default value is "2024-04-01".
+     Note that overriding this default value may result in unsupported behavior.
     :paramtype api_version: str
     :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
      Retry-After header is present.

sdk/healthinsights/azure-healthinsights-radiologyinsights/azure/healthinsights/radiologyinsights/_configuration.py

@@ -23,16 +23,15 @@ class RadiologyInsightsClientConfiguration:  # pylint: disable=too-many-instance
     :param endpoint: Supported Cognitive Services endpoints (protocol and hostname, for example:
      https://westus2.api.cognitive.microsoft.com). Required.
     :type endpoint: str
-    :param credential: Credential needed for the client to connect to Azure. Required.
+    :param credential: Credential used to authenticate requests to the service. Required.
     :type credential: ~azure.core.credentials.AzureKeyCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2023-09-01-preview". Note that overriding this default value may result in unsupported
-     behavior.
+    :keyword api_version: The API version to use for this operation. Default value is "2024-04-01".
+     Note that overriding this default value may result in unsupported behavior.
     :paramtype api_version: str
     """
 
     def __init__(self, endpoint: str, credential: AzureKeyCredential, **kwargs: Any) -> None:
-        api_version: str = kwargs.pop("api_version", "2023-09-01-preview")
+        api_version: str = kwargs.pop("api_version", "2024-04-01")
 
         if endpoint is None:
             raise ValueError("Parameter 'endpoint' must not be None.")