Merge pull request #241744 from msjasteppe/concepts-edits

Minor edits

Author: American-Dipper

articles/healthcare-apis/iot/concepts-machine-learning.md

@@ -5,7 +5,7 @@ author: msjasteppe
 ms.service: healthcare-apis
 ms.subservice: fhir
 ms.topic: conceptual
-ms.date: 04/28/2023
+ms.date: 06/15/2023
 ms.author: jasteppe
 ---
 
@@ -18,7 +18,7 @@ In this article, we explore using the MedTech service and the Azure Machine Lear
 
 ## The MedTech service and Azure Machine Learning Service reference architecture
 
-The MedTech service enables IoT devices to seamless integration with FHIR services. This reference architecture is designed to accelerate adoption of Internet of Things (IoT) projects. This solution uses Azure Databricks for the Machine Learning (ML) compute. However, Azure Machine Learning Services with Kubernetes or a partner ML solution could fit into the Machine Learning Scoring Environment.
+The MedTech service enables IoT devices to seamlessly integrate with FHIR services. This reference architecture is designed to accelerate adoption of Internet of Things (IoT) projects. This solution uses Azure Databricks for the Machine Learning (ML) compute. However, Azure Machine Learning Services with Kubernetes or a partner ML solution could fit into the Machine Learning Scoring Environment.
 
 The four line colors show the different parts of the data journey.
 
@@ -29,32 +29,35 @@ The four line colors show the different parts of the data journey.
 
 :::image type="content" source="media/concepts-machine-learning/iot-connector-machine-learning.png" alt-text="Screenshot of the MedTech service and Machine Learning Service reference architecture." lightbox="media/concepts-machine-learning/iot-connector-machine-learning.png":::
 
-**Data ingest – Steps 1 through 5**
+## Data ingest: Steps 1 - 5
 
 1. Data from IoT device or via device gateway sent to Azure IoT Hub/Azure IoT Edge.
 2. Data from Azure IoT Edge sent to Azure IoT Hub.
 3. Copy of raw IoT device data sent to a secure storage environment for device administration.
-4. PHI IoT payload moves from Azure IoT Hub to the MedTech service. The MedTech service icon represents multiple Azure services.
-5. Three parts to number 5: 
- a. The MedTech service requests Patient resource from the FHIR service. 
- b. The FHIR service sends Patient resource back to the MedTech service. 
- c. IoT Patient Observation is record in the FHIR service.
+4. IoT payload moves from Azure IoT Hub to the MedTech service. The MedTech service icon represents multiple Azure services.
+5. Three parts to number five: 
+   1. The MedTech service requests Patient resource from the FHIR service. 
+   2. The FHIR service sends Patient resource back to the MedTech service. 
+   3. IoT Patient Observation is record in the FHIR service.
 
-**Machine Learning and AI Data Route – Steps 6 through 11**
+## Machine Learning and AI Data Route: Steps 6 - 11
 
 6. Normalized ungrouped data stream sent to an Azure Function (ML Input).
 7. Azure Function (ML Input) requests Patient resource to merge with IoT payload.
-8. IoT payload with PHI is sent to an event hub for distribution to Machine Learning compute and storage.
-9. PHI IoT payload is sent to Azure Data Lake Storage Gen 2 for scoring observation over longer time windows.
-10. PHI IoT payload is sent to Azure Databricks for windowing, data fitting, and data scoring.
-11. The Azure Databricks requests more patient data from data lake as needed. a. Azure Databricks also sends a copy of the scored data to the data lake.
+8. IoT payload is sent to an event hub for distribution to Machine Learning compute and storage.
+9. IoT payload is sent to Azure Data Lake Storage Gen 2 for scoring observation over longer time windows.
+10. IoT payload is sent to Azure Databricks for windowing, data fitting, and data scoring.
+11. The Azure Databricks requests more patient data from data lake as needed.
+    1. Azure Databricks also sends a copy of the scored data to the data lake.
 
-**Notification and Care Coordination – Steps 12 - 18**
+## Notification and Care Coordination: Steps 12 - 18
 
 **Hot path**
 
 12. Azure Databricks sends a payload to an Azure Function (ML Output).
-13. RiskAssessment and/or Flag resource submitted to FHIR service. a. For each observation window, a RiskAssessment resource is submitted to the FHIR service. b. For observation windows where the risk assessment is outside the acceptable range a Flag resource should also be submitted to the FHIR service.
+13. RiskAssessment and/or Flag resource submitted to FHIR service. 
+    1. For each observation window, a RiskAssessment resource is submitted to the FHIR service. 
+    2. For observation windows where the risk assessment is outside the acceptable range a Flag resource should also be submitted to the FHIR service.
 14. Scored data sent to data repository for routing to appropriate care team. Azure SQL Server is the data repository used in this design because of its native interaction with Power BI.
 15. Power BI Dashboard is updated with Risk Assessment output in under 15 minutes.
 
@@ -73,4 +76,14 @@ For an overview of the MedTech service, see
 > [!div class="nextstepaction"]
 > [What is the MedTech service?](overview.md)
 
+To learn about the MedTech service device message data transformation, see
+
+> [!div class="nextstepaction"]
+> [Understand the MedTech service device data processing stages](overview-of-device-data-processing-stages.md)
+
+To learn about methods for deploying the MedTech service, see
+
+> [!div class="nextstepaction"]
+> [Choose a deployment method for the MedTech service](deploy-new-choose.md)
+
 FHIR® is a registered trademark of Health Level Seven International, registered in the U.S. Trademark Office and is used with their permission.

articles/healthcare-apis/iot/concepts-power-bi.md

@@ -5,7 +5,7 @@ author: msjasteppe
 ms.service: healthcare-apis
 ms.subservice: fhir
 ms.topic: conceptual
-ms.date: 04/28/2023
+ms.date: 06/15/2023
 ms.author: jasteppe
 ---
 
@@ -14,13 +14,13 @@ ms.author: jasteppe
 > [!NOTE]
 > [Fast Healthcare Interoperability Resources (FHIR®)](https://www.hl7.org/fhir/) is an open healthcare specification.
 
-In this article, we explore using the MedTech service and Microsoft Power Business Intelligence (BI).
+In this article, we explore using the MedTech service and Microsoft Power Business Intelligence (Power BI).
 
 ## The MedTech service and Power BI reference architecture
 
 This reference architecture shows the basic components of using the Microsoft cloud services to enable Power BI on top of Internet of Things (IoT) and FHIR data.
 
-You can even embed Power BI dashboards inside the Microsoft Teams client to further enhance care team coordination. For more information on embedding Power BI in Teams, visit [here](/power-bi/collaborate-share/service-embed-report-microsoft-teams).
+You can even embed Power BI dashboards inside the Microsoft Teams client to further enhance care team coordination. For more information on embedding Power BI in Teams, see [Embed Power BI content in Microsoft Teams](/power-bi/collaborate-share/service-embed-report-microsoft-teams).
 
 :::image type="content" source="media/concepts-power-bi/iot-connector-power-bi.png" alt-text="Screenshot of the MedTech service and Power BI." lightbox="media/concepts-power-bi/iot-connector-power-bi.png":::
 
@@ -45,4 +45,14 @@ For an overview of the MedTech service, see
 > [!div class="nextstepaction"]
 > [What is the MedTech service?](overview.md)
 
+To learn about the MedTech service device message data transformation, see
+
+> [!div class="nextstepaction"]
+> [Understand the MedTech service device data processing stages](overview-of-device-data-processing-stages.md)
+
+To learn about methods for deploying the MedTech service, see
+
+> [!div class="nextstepaction"]
+> [Choose a deployment method for the MedTech service](deploy-new-choose.md)
+
 FHIR® is a registered trademark of Health Level Seven International, registered in the U.S. Trademark Office and is used with their permission.

articles/healthcare-apis/iot/concepts-teams.md

@@ -5,7 +5,7 @@ author: msjasteppe
 ms.service: healthcare-apis
 ms.subservice: fhir
 ms.topic: conceptual
-ms.date: 04/28/2023
+ms.date: 06/15/2023
 ms.author: jasteppe
 ---
 
@@ -22,7 +22,7 @@ When combining the MedTech service, the FHIR service, and Teams, you can enable
 
 The diagram is a MedTech service to Teams notifications conceptual architecture for enabling the MedTech service, the FHIR service, and the Teams Patient App.
 
-You can even embed Power BI Dashboards inside the Microsoft Teams client. For more information on embedding Power BI in Microsoft Team visit [here](/power-bi/collaborate-share/service-embed-report-microsoft-teams).
+You can even embed Power BI Dashboards inside the Microsoft Teams client. For more information on embedding Power BI in Microsoft Team, see [Embed Power BI content in Microsoft Teams](/power-bi/collaborate-share/service-embed-report-microsoft-teams).
 
 :::image type="content" source="media/concepts-teams/iot-connector-teams.png" alt-text="Screenshot of the MedTech service and Teams." lightbox="media/concepts-teams/iot-connector-teams.png":::
 
@@ -47,4 +47,14 @@ For an overview of the MedTech service, see
 > [!div class="nextstepaction"]
 > [What is the MedTech service?](overview.md)
 
+To learn about the MedTech service device message data transformation, see
+
+> [!div class="nextstepaction"]
+> [Understand the MedTech service device data processing stages](overview-of-device-data-processing-stages.md)
+
+To learn about methods for deploying the MedTech service, see
+
+> [!div class="nextstepaction"]
+> [Choose a deployment method for the MedTech service](deploy-new-choose.md)
+
 FHIR® is a registered trademark of Health Level Seven International, registered in the U.S. Trademark Office and is used with their permission.