title: Probabilistic graphic models applied to identification of diseases.
abstract: Decision-making is fundamental when making diagnosis or choosing treatment. The broad dissemination of computed systems and databases allows systematization of part of decisions through artificial intelligence. In this text, we present basic use of probabilistic graphic models as tools to analyze causality in health conditions. This method has been used to make diagnosis of Alzheimer´s disease, sleep apnea and heart diseases.
authors.affiliation: Universidade Federal de São Paulo, São Paulo, SP, Brazil.
authors.forename: Renato Cesar
authors.initials: RC
authors.lastname: Sato
authors.affiliation: Centro Técnico Aeroespacial, São José dos Campos, SP, Brazil.
authors.forename: Graziela Tiemy Kajita
authors.initials: GT
authors.lastname: Sato
mesh_terms: D001185:Artificial Intelligence; D001499:Bayes Theorem; D003657:Decision Making; D003661:Decision Support Techniques; D003933:Diagnosis; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D015233:Models, Statistical