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This study validates the practical utility of quantum machine learning frameworks, specifically angle encoding techniques, in handling complex clinical datasets where classical models may struggle. By achieving over 90% accuracy in heart disease prediction, the research demonstrates a tangible pathway for quantum algorithms to enhance healthcare analytics beyond current conventional limits.
FAU’s quantum model predicts heart disease with 90% accuracy

Florida Atlantic University’s Arslan Munir, Ph.D., led research developing a quantum machine learning framework for heart disease prediction, achieving over 90% accuracy.
Florida Atlantic University researchers report achieving 90.26% accuracy in predicting heart disease using a novel Quantum Support Vector Machine with Angle Encoding. The study, published in the MDPI…
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