INTEGRATING PHYSIOLOGICAL MODELS WITH ARTIFICIAL INTELLIGENCE IN DIGITAL MEDICINE

Abstract

The integration of physiological models with artificial intelligence (AI) offers a promising framework for advancing digital medicine by combining mechanistic biological knowledge with data-driven intelligence. Physiological models describe human organ functions and system dynamics, while AI methods, including machine learning and deep learning, enable the analysis of complex and large-scale clinical data. Their integration improves the accuracy, interpretability, and personalization of digital healthcare solutions. Such hybrid systems support early disease detection, treatment optimization, and real-time patient monitoring. Applications are particularly relevant in cardiovascular and metabolic disease management. However, challenges remain in terms of data quality, model validation, and clinical implementation. Addressing these issues is essential for developing reliable, transparent, and patient-centered digital medical systems.