Computer analysis of atypical urothelial cells. I. Classification by supervised learning algorithms.
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.
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*