title: Artificial neural networks in the diagnosis of acute appendicitis.
abstract: The aim of the study was to assess the role of artificial neural networks in the diagnosis of acute appendicitis in patients presenting with right lower abdominal pain. Data from 156 patients presenting with suspected appendicitis over a 12-month period to a rural hospital were collected prospectively. The sensitivity, specificity, and positive and negative predictive values of the artificial neural network were 100%, 97.2%, 96.0%, and 100% respectively. Artificial neural networks can be an effective tool for accurately diagnosing acute appendicitis and may reduce unnecessary appendectomies.
authors: Ordu State Hospital, 52000, Ordu, Turkey.
authors: Ömer
authors: Ö
authors: Yoldaş
authors: Mesut
authors: M
authors: Tez
authors: Turgut
authors: T
authors: Karaca
mesh_terms: D000293:Adolescent; D000328:Adult; D001062:Appendectomy; D001064:Appendicitis / Q000175:diagnosis* / Q000601:surgery; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D055815:Young Adult