Models vs. Experts #9: Diagnosing Acute Abdominal Pain
Computer-aided diagnosis of acute abdominal pain
- De Dombal, F. T., Leaper, D. J., Staniland, J. R., McCann, A. P., & Horrocks, J. C.
- British Medical Journal, 2, 9-13
- An online version of the paper can be found here
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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 (79·6%). It is suggested as a result of these studies that the provision of such a system to aid the clinician is both feasible in a real-time clinical setting, and likely to be of practical value, albeit in a small percentage of cases.
The authors examine patients with acute abdnominal pain admitted into the professorial surgical unit in the General Infirmary at Leeds.
Here is how the test works
- Tabulate diagnosis from the clinical team, the house surgeon’s diagnosis, and any senior members of the team who saw the patient. (“human” estimates and analysis)
- Case history were entered into a computing system to produce a real-time diagnosis.
- Compare diagnosis across humans and the computer.
Here are the categories considered (many of which are abbreviated in subsequent tables):
First, a look at how the computer stacks up against the “experts,” aka, the senior clinician to the see the case:
Ouch. Computers trounce the top brains.
Thoughts on the paper?
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Definitions of common statistics used in our analysis are available here (towards the bottom)