title: Bayesian-based diagnostic decision-support for pediatrics.
abstract: The goal of this project was to develop a Pediatric Decision Support system (PDS) that allows a resident physician to define a patient case based on symptoms (diagnostic signs and test results) and generates a list of possible diagnoses based on the World Health Organization's International Classification of Diseases (ICD10). The intent is to improve the diagnostic approach taken by resident physicians and eventually become a training tool in medical education programs.
authors.affiliation: Systems and Computer Engineering, Carleton University, Canada. cpyper@connect.carleton.ca.com
authors.forename: C
authors.initials: C
authors.lastname: Pyper
authors.forename: M
authors.initials: M
authors.lastname: Frize
authors.forename: G
authors.initials: G
authors.lastname: Lindgaard
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D003196:Computer Graphics; D003198:Computer Simulation; D003657:Decision Making; D020000:Decision Support Systems, Clinical; D003661:Decision Support Techniques; D006801:Humans; D020407:Internet; D015233:Models, Statistical; D010372:Pediatrics / Q000193:education / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software; D018511:Systems Integration; D014584:User-Computer Interface