Time to Trade in Your Doctor for an Algo?

Time to Trade in Your Doctor for an Algo?

August 3, 2014 Behavioral Finance
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(Last Updated On: January 18, 2017)

Artificial intelligence in the diagnosis of low-back pain and sciatica

  • Mathew, B., Norris, D., Hendry, D., & Waddell, G.
  • Spine, 13, 168-172
  • An online version of the paper can be found here
  • Want a summary of academic papers with alpha? Check out our free Academic Alpha Database!

Abstract:

In a prospective trial of 200 patients with low-back pain or sciatica, the diagnostic performance of a computer was compared with that of a clinician in a variety of clinical settings. The results indicate that artificial Intelligence techniques can be used for the differential diagnosis of low-back disorders, can outperform clinicians, and can be used to develop better methods of human differential diagnosis.

Experimental design:

The sample contained 200 patients, with 50 in each of the four diagnostic categories:

  1. simple low-back pain
  2. root pain
  3. spinal pathology
  4. abnormal illness behavior.

These patients were analyzed by doctors, which were classified into 3 groups:

  • Full assessment: hospital doctors with access to special investigations;
  • Clinical assessment: family doctors based in the community;
  • Systematic assessment: limited to a set of symptoms only.

The computer system used 2 diagnostic methods based on Fuzzy Logic:

  • No-dialogue diagnosis: Data is entered into the computer and the  diagnosis is computed;
  • Dialogue diagnosis: The computer asks questions of the patient until it is confident it has a diagnosis.

Some insight into the algo:

The table below highlights how the computer dynamically develops a checklist approach to determining a diagnosis for a particular category of back pain.

lowbackalgo

Here is the finding:

  • The computer outperformed the clinicians.

table

Still Trust your Doctor?


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Definitions of common statistics used in our analysis are available here (towards the bottom)




About the Author

Tian Yao

Prior to joining the Alpha Architect team, Ms. Yao was a Research Assistant to Dr. Gray. She studied quantitative models and summarized over 200 academic articles on psychology and behavioral finance. Her prior experience includes work as a financial analyst at United Asset Growth (China) LLC, and as a business development intern for Shanghai Pudong Development Bank. Tian earned a Masters in Finance at Drexel University. She earned her Bachelors degree in Finance at Nanjing Normal University, China.


  • Michael Milburn

    It’s interesting that the no-dialogue AI is better than the dialogue-based AI.