title: Analyzing diaries for analytical relapse prevention using natural induction: a method and preliminary results.
abstract: This article briefly describes natural induction approach to knowledge discovery, and then applies it to the problem of bad habit relapse prevention by analyzing patients' diaries. Natural induction seeks patterns in data that are in forms easy to understand and interpret, because they resemble those in which humans represent knowledge, such as natural language descriptions and visual forms. The application of natural induction to the problem of bad habit relapse has produced patterns easy to understand, in some cases of surprising simplicity.
authors.affiliation: Machine Learning and Inference Laboratory, Center for Discovery Science and Health Informatics, George Mason University, Fairfax, Virginia 22030, USA. jwojt@mli.gmu.edu
authors.forename: Janusz
authors.initials: J
authors.lastname: Wojtusiak
authors.forename: Ryszard S
authors.initials: RS
authors.lastname: Michalski
mesh_terms: D000465:Algorithms; D015438:Health Behavior; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D009765:Obesity / Q000517:prevention & control; D010358:Patient Participation / Q000379:methods; D012008:Recurrence; D013223:Statistics as Topic / Q000379:methods*