Implementation of a medical diagnosis recommendation system

Abstract

Medical diagnosis represents a central and essential cognitive task for determining a patient's condition and suggesting appropriate treatment. Diagnostic accuracy is fundamental in global healthcare systems. Although crucial, this process can be subject to challenges related to case complexity and practitioners' cognitive load. To support this demanding task, recommender systems, derived from artificial intelligence, offer an innovative approach. This project focuses on the implementation of a recommender system specifically dedicated to medical diagnosis. The objective is to provide a decision support tool for physicians, assisting them in diagnosis and prognosis by transforming uncertainty into near-certainty. Such a system aims to improve the quality of medical decisions, reduce the risk of physician fatigue related to intensive work, and overcome the shortage of specialist physicians, thus overcoming some potential limitations of traditional approaches