Author

Y. Banad

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Open access Sep 2026

Comparing the use of supervised machine learning variable selection methods in the context of two-group classification in the psychological and health sciences

Introduction Variable selection (VS) is crucial for building accurate and generalizable classification models. Reducing the necessary number of variables improves model efficiency, interpretability, and generalizability while reducing data collection burden. Despite the availability of various VS methods, their compara...

Catherine M. Bain, Ding-Jing Shi, Y. Banad et al. · Frontiers in Psychology · 0 citations

Review Jul 2026

A clinically grounded taxonomy and systematic review of artificial intelligence for cardiovascular diagnosis: From machine learning to multimodal and agentic systems

Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, creating an urgent need for accurate, trustworthy, and clinically deployable artificial intelligence (AI) systems capable of supporting complex diagnostic decision-making. Although AI has advanced considerably in cardiovascular diagnosis, e...

Z. Rezaei, Mohammad Amin Amini, Y. Banad · Comput. Biol. Medicine · 0 citations