Computer-aided diagnosis of lower gastrointestinal tract disorders.

This paper reports a survey of human and computer-aided diagnosis in a prospective consecutive series of 301 patients admitted to the hospital with lower gastrointestinal tract disease. At initial outpatient contact (at which time endoscopy was customarily performed), the clinicians' diagnostic accuracy was 64.5%.

Human and computer-aided diagnosis of abdominal pain: further report with emphasis on performance of clinicians.

This paper reports a controlled trial of human and computer-aided diagnosis in a series of 552 patients with acute abdominal pain. The overall diagnostic accuracy of the computer-aided system was 91.5% and that of the senior clinician to see each case was 81.

Clinical diagnostic process: an analysis.

An analysis of observations made during 1,307 diagnoses by a total of 28 clinicians (503 diagnoses in real life, and 804 on simulated patients) concerned primarily the interview of patients suffering from abdominal pain. Interviews ranged from 10 to 35 questions, and from "stereotyped" procedures, in which identical (and often irrelevant) questions were asked to each patient, to "adaptive" interviews, in which specific relevant questions were put to each patient. Senior clinicians tended to ask fewer, more relevant questions than their junior counterparts; and urgent cases were dealt with in a more adaptive fashion than routine cases in outpatients.

Computer-assisted diagnosis of abdominal pain using "estimates" provided by clinicians.

This paper reports a comparison between two modes of computer-aided diagnosis in a real-time prospective trial involving 472 patients with acute abdominal pain. In the first mode the computer-aided system analysed each of the 472 patients by referring to data previously collated from a large series of 600 real-life patients. In the second mode the system used as a basis for its analysis "estimates" of probability provided by a group of six clinicians.

Computer-aided diagnosis of acute abdominal pain.

This paper reports a controlled prospective unselected real-time comparison of human and computer-aided diagnosis in a series of 304 patients suffering from abdominal pain of acute onset.The computing system's overall diagnostic accuracy (91.8%) was significantly higher than that of the most senior member of the clinical team to see each case (79.

Computer-aided diagnosis: description of an adaptable system, and operational experience with 2,034 cases.

This paper describes a system of computer-aided diagnosis using an English Electric KDF9 computer linked to a terminal in a busy clinical department. Data from a series of patients were recorded, coded, and entered into the computer, which then performed a Bayesian analysis and displayed diagnostic probabilities in an adaptable format. Experience in this setting suggests that computer diagnosis may be a valuable aid to the clinician.