Implant Insights: Accelerating Healthcare with Databricks

Project Overview

This project demonstrates the power of combining Databricks and xSIID implant chips to revolutionize medical data processing and analysis. By harnessing the capabilities of Databricks' powerful tools and the unique data streams from xSIID implants, we aim to:

• Extract valuable insights from diverse medical data types (images, documents, etc.).
• Accelerate medical research and enable faster, more informed clinical decisions.
• Enhance diagnostic accuracy and improve patient outcomes.

Key Features

• Seamless ingestion and processing of large-scale medical data using Databricks.
• Advanced image analysis and feature extraction with databricks-pixels.
• Machine learning model development and deployment with MLflow.
• Feature Store integration for efficient feature management and collaboration.
• Automated inference on new implant data.

Getting Started

1. Clone this repository.
2. Set up a Databricks workspace and configure necessary clusters.
3. Install the required libraries listed in requirements.txt.
4. Import the notebooks into your Databricks workspace.
5. Execute the notebooks in the following order:
   • data_ingestion.py
   • data_processing.py
   • model_training.py
   • model_deployment.py
6. Schedule jobs/scheduled_inference.py for automated inference.

FlowChart Images:

Contributing

We welcome contributions to improve and expand this project. Please feel free to open issues or submit pull requests.

Disclaimer

This project is for demonstration purposes only and should not be used in a clinical setting without proper validation and regulatory approvals.

License

This project is licensed under the MIT License.