Carotid Doppler Audio Dataset for Stroke Risk Prediction: 149 Recordings from 75 Patients
Description
Doppler audio analysis framework extracting 24 hemodynamic features with Smart Score (1-5) and Risk Score (0-1). Open dataset: 149 recordings from 75 patients with clinical metadata for stroke screening. Doppler_v1/ ├── README.md # Project overview, setup, usage, citation ├── LICENSE # MIT License ├── .gitignore # Excludes large dataset files ├── requirements.txt # Python dependencies ├── app.py # Main Flask web application ├── app.ipynb # Jupyter Notebook (algorithm development) ├── templates/ │ └── index.html # Web interface (Arabic/English) ├── PROCESSED/ │ ├── audio/ # Dataset: 149 WAV recordings (external link) │ ├── spectrum_images/ # Diagnostic PNG figures │ └── Result_Export/ # CSV/Excel reports with 24 features ├── dataset/ │ └── metadata.csv # Clinical annotations per recording └── docs/ └── user_manual.pdf # Platform usage guide
Files
Steps to reproduce
Clone repository and install dependencies: git clone + pip install -r requirements.txt Download dataset from Google Drive/Mendeley and place audio/ folder in PROCESSED/ directory Run Flask app: python app.py then open http://127.0.0.1:5000 in browser Upload WAV file, enter patient details, click process → view 24 features, Smart Score, Risk Score, and export reports