Estudio y selección de las técnicas de Inteligencia Artificial para el diagnóstico de enfermedades

Introduction: the process of diseases diagnosis is complex, given that medical data and information can often have uncertainty and require being treated with artificial intelligence (AI) techniques in order to assist patients’ diseases with greater assurance supporting the decision making. Objective: to compare artificial intelligence techniques that are frequently used for the diagnosis of diseases, when the data stored are kept on the behavior of diseases that frequently affect a population in question. Method: a research supported by the theory of discrete multicriteria decision support process, which is useful for the decision making, particularly in relation to the artificial intelligence techniques that best suits to perform the diagnosis of diseases with greater certainty. Results: Discrete Multicriteria Decision Making Theory is presented for decision making in relation to the artificial intelligence techniques that best suit the diagnosis of diseases with greater certainty. Conclusions: it was possible to identify the artificial intelligence techniques that well-suited the diagnosis of diseases with greater certainty, using Discrete Multicriteria Decision-making Theory, making possible the assessment of symptoms, signs and the risk factors presented in patients. DIAGNOSIS; ARTIFICIAL INTELLIGENCE; CERTAINTY