title: System for selecting relevant information for decision support.
abstract: We implemented a prototype of a decision support system called SIR which has a form of a web-based classification service for diagnostic decision support. The system has the ability to select the most relevant variables and to learn a classification rule, which is guaranteed to be suitable also for high-dimensional measurements. The classification system can be useful for clinicians in primary care to support their decision-making tasks with relevant information extracted from any available clinical study. The implemented prototype was tested on a sample of patients in a cardiological study and performs an information extraction from a high-dimensional set containing both clinical and gene expression data.
authors.affiliation: European Center for Medical Informatics, Statistics and Epidemiology, Czech Republic. kalina@cs.cas.cz
authors.forename: Jan
authors.initials: J
authors.lastname: Kalina
authors.forename: Libor
authors.initials: L
authors.lastname: Seidl
authors.forename: Karel
authors.initials: K
authors.lastname: Zvára
authors.forename: Hana
authors.initials: H
authors.lastname: Grünfeldová
authors.forename: Dalibor
authors.initials: D
authors.lastname: Slovák
authors.forename: Jana
authors.initials: J
authors.lastname: Zvárová
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D020000:Decision Support Systems, Clinical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D020407:Internet; D010363:Pattern Recognition, Automated / Q000379:methods*; D012984:Software; D014584:User-Computer Interface