fr-meyer/MD-ViSCo
MD-ViSCo: A Unified Model for Multi-Directional Vital Sign Waveform Conversion. IEEE JBHI 2026.
This project helps medical researchers and data scientists working with vital sign data to convert between different types of physiological waveforms like ECG, PPG, and ABP. You can input raw vital sign data and patient demographics to get transformed waveforms or predictions for blood pressure and atrial fibrillation. It is designed for those who need to analyze or simulate physiological signals.
Use this if you need to convert between different vital sign waveforms, predict blood pressure from these signals, or classify atrial fibrillation using a unified deep learning model.
Not ideal if you are looking for a plug-and-play clinical diagnostic tool or a solution for real-time patient monitoring.
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Language
Python
License
MIT
Category
Last pushed
Feb 10, 2026
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