title: Computer analysis of atypical urothelial cells. I. Classification by supervised learning algorithms.
abstract: Computer discrimination of atypical (ATY) urothelial cells from the urinary sediment by means of supervised learning algorithms discoled that these cells form a distinct, although ill-defined, family of cells which differs from normal (NEG) and malignant (POS) cell groups. The clinical significance of this observation must await long-term clinical follow-up. The possibility of issuing computer displays on individual patients with possible diagnostic and prognostic implications is discussed.
mesh_terms: D000368:Aged; D003201:Computers; D003581:Cytodiagnosis; D003936:Diagnosis, Computer-Assisted; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis*; D014556:Urine / Q000166:cytology*