Bridging Electrophysiology, Biophysics and Artificial Intelligence: Human-Centric Computational Modeling in Modern Medicine and Surgery

Modern medicine and surgery are experiencing a paradigm shift through the convergence of electrophysiology, biophysics, and artificial intelligence (AI). Electrophysiology provides the language of bioelectric signals, capturing the dynamics of excitable tissues such as the heart, brain, and muscles. Biophysics offers mechanistic insights into how these signals propagate through complex structures, integrating electrical, mechanical, and chemical processes into unified models of physiology. AI contributes powerful computational tools capable of learning from large datasets, identifying subtle patterns, and predicting outcomes with high accuracy. When these domains are bridged through human-centric computational modeling, the result is a transformative framework that enhances diagnosis, guides therapy, and supports surgical precision. This chapter explores the integration of electrophysiological data, biophysical principles, and AI algorithms into cohesive computational pipelines designed for clinical utility. Applications span cardiology, neurology, oncology, and surgery, where models can predict arrhythmias, monitor seizures, simulate tumor growth, and guide robotic interventions. Case studies highlight how hybrid approaches combining mechanistic equations with deep learning architectures provide both interpretability and predictive power. Challenges remain, including data scarcity, scalability, and ethical concerns such as bias and privacy. Yet emerging strategies such as federated learning, digital twins, and uncertainty quantification promise to address these limitations. By synthesizing electrophysiology, biophysics, and AI into human-centric computational models, medicine can become more precise, predictive, and personalized. This convergence advances scientific understanding, empowers clinicians, improves patient outcomes, and reshapes the practice of modern medicine and surgery.