Merge pull request #233574 from psanapathi/release-azure-health-insights

Update Onco Phenotype documentation within Azure Health Insights

Author: American-Dipper

articles/azure-health-insights/TOC.yml

@@ -6,7 +6,7 @@ items:
   items:
     - name: About Azure Health Insights
       href: overview.md
-    - name: Onco-Phenotype
+    - name: Onco Phenotype
       href: ./oncophenotype/index.yml
     - name: Trial Matcher 
       href: ./trial-matcher/index.yml

articles/azure-health-insights/deploy-portal.md

@@ -56,7 +56,7 @@ Once the Cognitive Services account is successfully created, configure private e
 To get started using Azure Health Insights, get started with one of the following models:
 
 >[!div class="nextstepaction"]
-> [Onco-Phenotype](oncophenotype/index.yml) 
+> [Onco Phenotype](oncophenotype/index.yml) 
 
 >[!div class="nextstepaction"]
 > [Trial Matcher](trial-matcher/index.yml) 

articles/azure-health-insights/index.yml

@@ -25,11 +25,11 @@ landingContent:
         links:
           - text: Deploy using the portal
             url: deploy-portal.md
-  - title: Onco-Phenotype
+  - title: Onco Phenotype
     linkLists:
       - linkListType: overview
         links:
-          - text: About Onco-Phenotype
+          - text: About Onco Phenotype
             url: oncophenotype/overview.md
       - linkListType: concept
         links:

articles/azure-health-insights/oncophenotype/TOC.yml

@@ -1,17 +1,15 @@
 items: 
-- name: Onco-Phenotype
+- name: Onco Phenotype
   href: index.yml
 - name: Overview
   expanded: true
   items:
-    - name: About Onco-Phenotype
+    - name: About Onco Phenotype
       href: overview.md
-    - name: FAQ
-      href: faq.md
 - name: Quickstarts
   expanded: true
   items:
-     - name: Use the Onco-Phenotype model
+     - name: Use the Onco Phenotype model
        href: get-started.md
 - name: Responsible use of AI
   expanded: true
@@ -20,22 +18,37 @@ items:
       href: /legal/azure-health-insights/oncophenotype/transparency-note?context=/azure/azure-health-insights/oncophenotype/context/context
     - name: Data, privacy, and security
       href: ../responsible-ai/data-privacy-security.md
+- name: Concepts
+  expanded: true
+  items:
+     - name: Model configuration
+       href: model-configuration.md
+     - name: Patient information
+       href: patient-info.md
+     - name: Inference information
+       href: inferences.md
+- name: Reference
+  expanded: true
+  items:
+     - name: REST API
+       href: /rest/api/cognitiveservices/healthinsights/onco-phenotype
+     - name: SDKs
+       items:
+        - name: .NET
+          href: /rest/api/cognitiveservices/healthinsights/onco-phenotype
+        - name: Java
+          href: /rest/api/cognitiveservices/healthinsights/onco-phenotype
+        - name: Python
+          href: /rest/api/cognitiveservices/healthinsights/onco-phenotype
 - name: Resources
   items:
+     - name: FAQ
+       href: faq.md
      - name: Enterprise readiness
        items:
         - name: Region Support
           href: https://azure.microsoft.com/explore/global-infrastructure/products-by-region/?products=cognitive-services
         - name: Compliance and certification
           href: https://azure.microsoft.com/support/legal/cognitive-services-compliance-and-privacy/
      - name: Support and help options
-       href: support-and-help.md
-- name: Concepts
-  expanded: true
-  items:
-     - name: Model configuration
-       href: model-configuration.md
-     - name: Patient information
-       href: patient-info.md
-     - name: Inference information
-       href: inferences.md
+       href: support-and-help.md

articles/azure-health-insights/oncophenotype/faq.md

@@ -1,7 +1,7 @@
 ---
-title: Onco-Phenotype frequently asked questions
+title: Onco Phenotype frequently asked questions
 titleSuffix: Azure Health Insights
-description: Onco-Phenotype frequently asked questions
+description: Onco Phenotype frequently asked questions
 services: azure-health-insights
 author: iBoonZ
 manager: urieinav
@@ -12,9 +12,7 @@ ms.author: behoorne
 ---
 
 
-# Onco-Phenotype Frequently Asked Questions
-
-You’ll find answers to commonly asked questions about Onco-Phenotype, part of Azure Health Insights service, in this article
+# Onco Phenotype Frequently Asked Questions
 
 - What does inference value `None` mean?
 
@@ -26,7 +24,7 @@ You’ll find answers to commonly asked questions about Onco-Phenotype, part of
 
 - Do you support behavior code along with histology code?
 
-  No, the OncoPhenotype API doesn't support 1-digit behavior code. Only 4-digit histology code is supported.
+  No, only four digit histology code is supported.
 
 - What does inference value `N+` mean for clinical/pathologic N category? Why don't you have `N1, N2, N3` inference values?
 

articles/azure-health-insights/oncophenotype/get-started.md

@@ -1,7 +1,7 @@
 ---
-title: Use Onco-Phenotype 
+title: Use Onco Phenotype 
 titleSuffix: Azure Health Insights
-description: This article describes how to use the Onco-Phenotype
+description: This article describes how to use the Onco Phenotype
 services: azure-health-insights
 author: iBoonZ
 manager: urieinav
@@ -12,12 +12,12 @@ ms.author: behoorne
 ---
 
 
-# Quickstart: Use the Onco-Phenotype model
+# Quickstart: Use the Onco Phenotype model
 
-This quickstart provides an overview on how to use the Onco-Phenotype.
+This quickstart provides an overview on how to use the Onco Phenotype.
 
 ## Prerequisites
-To use the Onco-Phenotype model, you must have a Cognitive Services account created. If you haven't already created a Cognitive Services account, see [Deploy Azure Health Insights using the Azure portal.](../deploy-portal.md)
+To use the Onco Phenotype model, you must have a Cognitive Services account created. If you haven't already created a Cognitive Services account, see [Deploy Azure Health Insights using the Azure portal.](../deploy-portal.md)
 
 Once deployment is complete, you use the Azure portal to navigate to the newly created Cognitive Services account to see the details, including your Service URL. The Service URL to access your service is: https://```YOUR-NAME```.cognitiveservices.azure.com/. 
 
@@ -26,7 +26,7 @@ Once deployment is complete, you use the Azure portal to navigate to the newly c
 
 To send an API request, you need your Cognitive Services account endpoint and key. You can also find a full view on the [request parameters here](../request-info.md)
 
-![Screenshot of the Keys and Endpoints for the Onco-Phenotype.](../media/keys-and-endpoints.png) 
+![Screenshot of the Keys and Endpoints for the Onco Phenotype.](../media/keys-and-endpoints.png) 
 
 > [!IMPORTANT]
 > Prediction is performed upon receipt of the API request and the results will be returned asynchronously. The API results are available for 24 hours from the time the request was ingested, and is indicated in the response. After this time period, the results are purged and are no longer available for retrieval.
@@ -35,7 +35,7 @@ To send an API request, you need your Cognitive Services account endpoint and ke
 
 ### Starting with a request that contains a case
 
-You can use the data from this example, to test your first request to the Onco-Phenotype model.
+You can use the data from this example, to test your first request to the Onco Phenotype model.
 
 ```url
 POST http://{cognitive-services-account-endpoint}/healthinsights/oncophenotype/jobs?api-version=2023-03-01-preview
@@ -70,7 +70,7 @@ Ocp-Apim-Subscription-Key: {cognitive-services-account-key}
 ```
 ### Evaluating a response that contains a case
 
-You get the status of the job by sending a request to the Onco-Phenotype model and adding the job ID from the initial request in the URL, as seen in the code snippet:
+You get the status of the job by sending a request to the Onco Phenotype model and adding the job ID from the initial request in the URL, as seen in the code snippet:
 
 ```url 
 GET http://{cognitive-services-account-endpoint}/healthinsights/oncophenotype/jobs/385903b2-ab21-4f9e-a011-43b01f78f04e?api-version=2023-03-01-preview
@@ -141,7 +141,7 @@ More information on the [response information can be found here](../response-inf
 
 ## Request validation
 
-Every request has required and optional fields that should be provided to the Onco-Phenotype model.
+Every request has required and optional fields that should be provided to the Onco Phenotype model.
 When you're sending data to the model, make sure that you take the following properties into account:
 
 Within a request:

articles/azure-health-insights/oncophenotype/index.yml

@@ -1,10 +1,10 @@
 ### YamlMime:Landing
 
-title: Onco-Phenotype documentation
-summary: Onco-Phenotype is offered within the context of the broader Azure Health Insights, augments traditional clinical NLP tools by enabling healthcare partners to rapidly identify key cancer attributes within their patient populations.
+title: Onco Phenotype documentation
+summary: Onco Phenotype is offered within the context of the broader Azure Health Insights, augments traditional clinical NLP tools by enabling healthcare partners to rapidly identify key cancer attributes within their patient populations.
 
 metadata:
-  title: Onco-Phenotype documentation
+  title: Onco Phenotype documentation
   titleSuffix: Azure Health Insights
   description: enable healthcare organizations to rapidly identify key cancer attributes within their patient populations.
   ms.service: Azure Health Insights
@@ -18,11 +18,11 @@ metadata:
 # linkListType: architecture | concept | deploy | download | get-started | how-to-guide | tutorial | overview | quickstart | reference | sample | tutorial | video | whats-new 
 
 landingContent:
-  - title: About Onco-Phenotype
+  - title: About Onco Phenotype
     linkLists:
       - linkListType: overview
         links:
-          - text: What is Onco-Phenotype?
+          - text: What is Onco Phenotype?
             url: overview.md
       - linkListType: concept
         links:
@@ -32,7 +32,7 @@ landingContent:
             url: patient-info.md
           - text: Inference information
             url: inferences.md
-  - title: Use the Onco-Phenotype model
+  - title: Use the Onco Phenotype model
     linkLists:
       - linkListType: quickstart
         links:

articles/azure-health-insights/oncophenotype/inferences.md

@@ -1,7 +1,7 @@
 ---
-title: Onco-Phenotype Inference information
+title: Onco Phenotype Inference information
 titleSuffix: Azure Health Insights
-description: This article provides Onco-Phenotype inference information.
+description: This article provides Onco Phenotype inference information.
 services: azure-health-insights
 author: iBoonZ
 manager: urieinav
@@ -12,9 +12,9 @@ ms.author: behoorne
 ---
 
 
-# Onco-Phenotype Inference information
+# Onco Phenotype Inference information
 
-Azure Health Insights Onco-Phenotype model was trained with labels that conform to the following standards.
+Azure Health Insights Onco Phenotype model was trained with labels that conform to the following standards.
 - Tumor site and histology inferences: **WHO ICD-O-3** representation.
 - Clinical and pathologic stage TNM category inferences: **American Joint Committee on Cancer (AJCC)'s 7th edition** of the cancer staging manual.
 

articles/azure-health-insights/oncophenotype/model-configuration.md

@@ -1,7 +1,7 @@
 ---
-title: Onco-Phenotype model configuration
+title: Onco Phenotype model configuration
 titleSuffix: Azure Health Insights
-description: This article provides Onco-Phenotype model configuration information.
+description: This article provides Onco Phenotype model configuration information.
 services: azure-health-insights
 author: iBoonZ
 manager: urieinav
@@ -12,9 +12,9 @@ ms.author: behoorne
 ---
 
 
-# Onco-Phenotype model configuration
+# Onco Phenotype model configuration
 
-To interact with the Onco-Phenotype model, you can provide several model configurations parameters that modify the outcome of the responses.
+To interact with the Onco Phenotype model, you can provide several model configurations parameters that modify the outcome of the responses.
 
 > [!IMPORTANT]
 > Model configuration is applied to ALL the patients within a request.
@@ -29,7 +29,7 @@ To interact with the Onco-Phenotype model, you can provide several model configu
 ## Case finding
 
 
-The Onco-Phenotype model configuration helps you find if any cancer cases exist. The API allows you to explicitly check if a cancer case exists in the provided clinical documents. 
+The Onco Phenotype model configuration helps you find if any cancer cases exist. The API allows you to explicitly check if a cancer case exists in the provided clinical documents. 
 
 **Check for cancer case** |**Did the model find a case?** |**Behavior** 
 ---------------------- |-----------------------|-------------------

articles/azure-health-insights/oncophenotype/overview.md

@@ -1,5 +1,5 @@
 ---
-title: What is Onco-Phenotype - Azure Health Insights
+title: What is Onco Phenotype - Azure Health Insights
 titleSuffix: Azure Health Insights
 description: Enable healthcare organizations to rapidly identify key cancer attributes within their patient populations.
 services: azure-health-insights
@@ -12,31 +12,31 @@ ms.author: behoorne
 ---
 
 
-# What is Onco-Phenotype - Azure Health Insights
+# What is Onco Phenotype - Azure Health Insights
 
-Onco-Phenotype is an AI model that’s offered within the context of the broader Azure Health Insights. It augments traditional clinical Natural Language Processing tools by enabling healthcare organizations to rapidly identify key cancer attributes within their patient populations.
+Onco Phenotype is an AI model that’s offered within the context of the broader Azure Health Insights. It augments traditional clinical Natural Language Processing tools by enabling healthcare organizations to rapidly identify key cancer attributes within their patient populations.
 
 
 > [!IMPORTANT] 
-> The Onco-Phenotype model is a capability provided “AS IS” and “WITH ALL FAULTS.” The Onco-Phenotype model isn't intended or made available for use as a medical device, clinical support, diagnostic tool, or other technology intended to be used in the diagnosis, cure, mitigation, treatment, or prevention of disease or other conditions, and no license or right is granted by Microsoft to use this capability for such purposes. This capability isn't designed or intended to be implemented or deployed as a substitute for professional medical advice or healthcare opinion, diagnosis, treatment, or the clinical judgment of a healthcare professional, and should not be used as such. The customer is solely responsible for any use of the Onco-Phenotype model. The customer is responsible for ensuring compliance with those license terms, including any geographic or other applicable restrictions.
+> The Onco Phenotype model is a capability provided “AS IS” and “WITH ALL FAULTS.” The Onco Phenotype model isn't intended or made available for use as a medical device, clinical support, diagnostic tool, or other technology intended to be used in the diagnosis, cure, mitigation, treatment, or prevention of disease or other conditions, and no license or right is granted by Microsoft to use this capability for such purposes. This capability isn't designed or intended to be implemented or deployed as a substitute for professional medical advice or healthcare opinion, diagnosis, treatment, or the clinical judgment of a healthcare professional, and should not be used as such. The customer is solely responsible for any use of the Onco Phenotype model. The customer is responsible for ensuring compliance with those license terms, including any geographic or other applicable restrictions.
 
 
-## Onco-Phenotype features
-The Onco-Phenotype model, available in the Azure Health Insights cognitive service as an API, augments traditional clinical natural language processing (NLP) tools by helping healthcare providers rapidly identify key attributes of a cancer within their patient populations with an existing cancer diagnosis. You can use this model to infer tumor site; histology; clinical stage tumor (T), node (N), and metastasis (M) categories; and pathologic stage TNM categories from unstructured clinical documents, along with confidence scores and relevant evidence.
+## Onco Phenotype features
+The Onco Phenotype model, available in the Azure Health Insights cognitive service as an API, augments traditional clinical natural language processing (NLP) tools by helping healthcare providers rapidly identify key attributes of a cancer within their patient populations with an existing cancer diagnosis. You can use this model to infer tumor site; histology; clinical stage tumor (T), node (N), and metastasis (M) categories; and pathologic stage TNM categories from unstructured clinical documents, along with confidence scores and relevant evidence.
 
 - **Tumor site** refers to the primary tumor location. 
 
 - **Histology** refers to the cell type of a given tumor.
 
 The following paragraph is adapted from  [American Joint Committee on Cancer (AJCC)'s Cancer Staging System](https://www.facs.org/quality-programs/cancer/ajcc/cancer-staging).
 
-Cancer staging describes the severity of an individual's cancer based on the magnitude of the original tumor, as well as on the extent cancer has spread in the body. The Onco-Phenotype model supports inferring two types of staging from the clinical documents - clinical staging and pathologic staging. They’re both expressed in the form of TNM categories, where TNM indicates the extent of the tumor (T), the extent of spread to the lymph nodes (N), and the presence of metastasis (M).
+Cancer staging describes the severity of an individual's cancer based on the magnitude of the original tumor, as well as on the extent cancer has spread in the body. The Onco Phenotype model supports inferring two types of staging from the clinical documents - clinical staging and pathologic staging. They’re both expressed in the form of TNM categories, where TNM indicates the extent of the tumor (T), the extent of spread to the lymph nodes (N), and the presence of metastasis (M).
 
 - **Clinical staging** determines the nature and extent of cancer based on the physical examination, imaging tests, and biopsies of affected areas. 
 
 - **Pathologic staging** can only be determined from individual patients who have had surgery to remove a tumor or otherwise explore the extent of the cancer. Pathologic staging combines the results of clinical staging (physical exam, imaging test) with surgical results. 
 
-The Onco-Phenotype model enables cancer registrars to efficiently abstract cancer patients as it infers the above-mentioned key cancer attributes from unstructured clinical documents along with evidence that are relevant to those attributes. Leveraging this API can reduce the manual time spent combing through large amounts of patient documentation by focusing on the most relevant content in support of a clinician.
+The Onco Phenotype model enables cancer registrars to efficiently abstract cancer patients as it infers the above-mentioned key cancer attributes from unstructured clinical documents along with evidence that are relevant to those attributes. Leveraging this API can reduce the manual time spent combing through large amounts of patient documentation by focusing on the most relevant content in support of a clinician.
 
 
 ## Language support
@@ -50,7 +50,7 @@ The Official prices will be released after public preview
 
 ## Next steps
 
-Get started using the Onco-Phenotype model:
+Get started using the Onco Phenotype model:
 
 >[!div class="nextstepaction"]
 > [deploy the service via the portal](../deploy-portal.md)