A Patient Community in Silico for Simulation of Major Disease Epidemiology, Progression, and Complications: Effect of Prophylaxis, Treatment, and Aging

Development of clinical expertise and improvement in patient safety can be accomplished by a physician only after prolonged experience with disease management while maintaining a life-long learning aptitude. In the current... [ view full abstract ]

Development of clinical expertise and improvement in patient safety can be accomplished by a physician only after prolonged experience with disease management while maintaining a life-long learning aptitude. In the current system of medical education with live patients, standardized patients, or human simulators, it is impractical to expose students to this longitudinal learning process because of the brevity of encounters and temporal limits of the educational experience. We hypothesize that a virtual patient community in silico with time-machine capabilities to control natural history, prophylaxis and treatment, and incorporating neural network-modeling with individual patients as nodes and epidemiologic, pathogenetic and other factors as connectors and incorporating elements of artificial intelligence would allow the students to follow the progression of major diseases through the lifetime of their virtual patients and to experience the effects of their management within the first three years of their study.