Stroke is a leading cause of mortality and disability worldwide, with a significant burden in low resource healthcare settings. Limited access to advanced diagnostic equipment in many primary healthcare centers can delay timely identification and intervention.
This project presents an offline Clinical Decision Support System (CDSS) for stroke risk prediction using structured patient data. The system leverages machine learning models trained on publicly available datasets to assist healthcare practitioners in identifying high-risk cases.
- Hugging face
- Kaggle
First clone the repo
git clone https://github.com/Laplace0xx/scdss.git
cd scdss
Install dependencies
uv sync
Run the application
uv run python src/ui/main.py
This project is licensed under the Apache License