Computer-assisted diagnosis of acute azotemia.
We designed a computer program to make diagnostic suggestions in cases of acute azotemia. The performance of the program was tested in a retrospective manner on 63 patients with acute azotemia. The program correctly identified 90 of 94 diagnoses and made 20 false positive diagnostic suggestions. A revised version of the program correctly identified 94 of 94 diagnoses and made 4 false negative suggestions. The justification for this kind of diagnostic aid is discussed.
D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted; D003951:Diagnostic Errors; D005069:Evaluation Studies as Topic; D006801:Humans; D008838:Microcomputers; D012984:Software; D014511:Uremia / Q000209:etiology*