IMPACT OF ARTIFICIAL INTELLIGENCE ON MEDICINE: BIBLIOGRAPHICAL REVIEW ON DIAGNOSIS, TREATMENT AND DECISION SUPPORT SYSTEMS

Abstract

The use of artificial intelligence (AI) in medicine has grown substantially, impacting areas such as imaging diagnosis, treatment prediction, and electronic medical record analysis. This literature review aimed to explore the use of AI in the diagnosis and treatment of diseases, highlighting methodologies and applications in different areas of health. Fifty-seven articles on the integration of AI in oncology, cardiology, and emergency medicine were analyzed. AI has been widely applied in clinical decision support systems, such as dynamic Bayesian networks to predict disease progression and treatment outcomes. The review revealed benefits, such as greater diagnostic accuracy and efficiency, but challenges related to transparency and trust in AI models persist. Many studies have employed machine learning and deep learning, integrating longitudinal data from medical records. It is concluded that AI has the potential to transform medical practice, but requires rigorous validation and supervision.