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This project uses a sample dataset of chest X-rays from the NIH to train a CNN model. The goal is for the model to learn how to detect anomolies and areas of interest.
Other components of the solution include:
- Sample EMR dashboard to view patient details
- Chestist web interface SMART on FHIR app to work with Chestist data in the context of a selected patient
- Imaging-API Azure Function to securely fetch images from an Azure Storage account
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 https://cla.opensource.microsoft.com.
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This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.
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