FFR Prediction & Coronary Artery Diagnosis
Apr 1, 2022
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1 min read
Overview
Developed an optimized FFR (Fractional Flow Reserve) prediction algorithm that incorporates hemodynamic flow features and biometric data, addressing limitations of conventional AI-based coronary diagnosis that relied solely on vessel imaging.
Key Contributions
- Incorporated hemodynamic features beyond vessel imaging
- Synthetic model generation for training data augmentation
- Improved prediction accuracy in the diagnostic gray zone
- Biometric data integration for patient-specific assessment
Authors
PhD Candidate
I develop AI-driven non-invasive biomarker prediction systems using
photoplethysmography (PPG) signals, bridging computational fluid dynamics
and deep learning for clinical diagnostics. My recent work on physics-integrated
blood viscosity assessment was published in Computer Methods and Programs
in Biomedicine (2025).