title: A genetic algorithm approach to multi-disorder diagnosis.
abstract: One of the common limitations of expert systems for medical diagnosis is that they make an implicit assumption that multiple disorders do not co-occur in a single patient. The need for this simplifying assumption stems from the fact that finding minimal sets of disorders that cover all symptoms for a given patient is generally computationally intractable (NP-hard). In this paper, we explain the need for performing multi-disorder diagnosis, review previous approaches, formulate the problem using set theory notation, and propose the use of a search method based on a genetic algorithm. We test the algorithm and compare it to another approach using a simple example. The genetic algorithm performs well independently of the order of symptoms, and has the potential to perform multi-disorder diagnosis using existing or newly developed knowledge bases.
authors.affiliation: Division of Health Sciences and Technology, Harvard Medical School/Massachusetts Institute of Technology, Cambridge, MA, USA. staalv@idi.ntnu.no
authors.forename: S
authors.initials: S
authors.lastname: Vinterbo
authors.forename: L
authors.initials: L
authors.lastname: Ohno-Machado
mesh_terms: D000465:Algorithms; D030342:Genetic Diseases, Inborn / Q000175:diagnosis*; D005826:Genetics, Medical; D006801:Humans