title: A visual fuzzy cluster system for patient analysis.
abstract: A visual fuzzy cluster (VFC) system is developed to assist physicians in interactively detecting and refining cluster partitions for patients with acute upper respiratory infections. The VFC system assists physicians in discovering relationships among patients by applying a fuzzy cluster algorithm to analyse a case base of patient findings. The algorithm discovers similarities among patients, while at the same time identifying atypical patients. The system visually presents the fuzzy cluster solutions on a three-dimensional animated display. Physicians then interactively manipulate icons representing patients to explore and refine the fuzzy cluster solution. Initial experiences with the VFC prototype are encouraging and support the claims that the system improves physician understanding and allows physicians to take advantage of visual recognition and manipulation skills to define and label patient groupings. The resulting labels and cluster centres or prototypes offer insight into the set of patient features that best discriminate between groups.
authors.affiliation: College of Business Administration, University of Northern Colorado, Greeley 80639.
authors.forename: T A
authors.initials: TA
authors.lastname: Sedbrook
authors.forename: H
authors.initials: H
authors.lastname: Wright
authors.forename: R
authors.initials: R
authors.lastname: Wright
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D003196:Computer Graphics; D003198:Computer Simulation; D005103:Expert Systems; D017143:Fuzzy Logic; D006801:Humans; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012120:Respiration Disorders / Q000175:diagnosis*; D014218:Triage / Q000379:methods; D014584:User-Computer Interface