dummy edits to update build

Author: msakande

articles/ai-studio/how-to/healthcare-ai/deploy-cxrreportgen.md

@@ -194,9 +194,11 @@ Response payload is a JSON formatted string containing the following fields:
 ```
 
 ### Supported image formats
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 The deployed model API supports images encoded in PNG or JPEG formats. For optimal results, we recommend using uncompressed/lossless PNGs with 8-bit monochromatic images.
 
 ## Learn more from samples
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 CXRReportGen is a versatile model that can be applied to a wide range of tasks and imaging modalities. For more examples see the following interactive Python notebook: 
 
 * [Deploying and Using CXRReportGen](https://aka.ms/healthcare-ai-examples-cxr-deploy): Learn how to deploy the CXRReportGen model and integrate it into your workflow. This notebook also covers bounding-box parsing and visualization techniques.

articles/ai-studio/how-to/healthcare-ai/deploy-medimageinsight.md

@@ -231,6 +231,7 @@ MedImageInsight is a versatile model that can be applied to a wide range of task
 * [Enhancing Classification with Adapter Networks](https://aka.ms/healthcare-ai-examples-mi2-adapter): Improve classification performance by building a small adapter network on top of MedImageInsight.
 
 #### Advanced applications
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 * [Inferring MRI Acquisition Parameters from Pixel Data](https://aka.ms/healthcare-ai-examples-mi2-exam-parameter): Understand how to extract MRI exam acquisition parameters directly from imaging data.
 
 * [Scalable MedImageInsight Endpoint Usage](https://aka.ms/healthcare-ai-examples-mi2-advanced-call): Learn how to generate embeddings of medical images at scale using the MedImageInsight API while handling potential network issues gracefully.

articles/ai-studio/how-to/healthcare-ai/deploy-medimageparse.md

@@ -192,6 +192,7 @@ Response payload is a list of JSON-formatted strings, each corresponding to a su
 ```
 
 ### Supported image formats
+
 The deployed model API supports images encoded in PNG format. For optimal results, we recommend using uncompressed/lossless PNGs with RGB images.
 
 As described in the API specification, the model only accepts images in the resolution of `1024x1024`pixels. Images need to be resized and padded (in the case of non-square aspect ratio).