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Machine Learning Techniques for the Performance Enhancement of Multiple Classifiers in the Detection of Cardiovascular Disease from PPG Signals

Engineering and Technology

Machine Learning Techniques for the Performance Enhancement of Multiple Classifiers in the Detection of Cardiovascular Disease from PPG Signals

S. W. Rabkin, A. Cataldo, et al.

This groundbreaking research conducted by Simon W Rabkin, Andrea Cataldo, Sivamani Palanisamy, and Harikumar Rajaguru utilizes advanced machine learning techniques to enhance the detection of cardiovascular diseases through photoplethysmography signals. With an impressive accuracy of 98.31%, their innovative approach significantly improves the potential for timely diagnoses of CVD.

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