Models vs. Experts #13: Let the Computer Decide who is Suicidal?
A probabilistic system for identifying suicide attempters
- Gustafson, D. H., Greist, J. H., etal
- Computers and Biomedical Research, I0, 1-7
- 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!
This paper reports the results of a study to develop and pilot test a system for screening potential suicide attempters. The system includes a computer interview of patients complaining of suicidal thoughts and Bayesian processing (using subjective probability estimation) of the results of that interview. The results suggest that the system may significantly improve the health field’s ability to identify suicide attempters.
The authors make a hypothesis that people could develop a system to identify patients who will attempt suicide that was significantly better than the average clinician.
Firstly, they develop a system to identify suicide attempters:
- Patients are asked to go over a computer interview (questions omitted here);
- Immediately after the interview the computer generates an estimate of probability of a suicide attempt.
- Bayes’s theorem is used as the data processing model for this system.
The authors compare computer-based probabilities against human-based probabilities. This analysis is confusing and hard to understand, but the bottomline result is that computer’s have an edge.
Later in the paper the authors talk about a study they are working on that is run like a typical controlled experiment:
- Patients are interviewed by a computer and a human.
- Computers make predictions and humans make predictions about suicide attempts.
- Compare the performance.
The sample size is only 30 patients, but here are the results:
- The computer identified 75% of the attemptors; the humans identified 22%.
Would you rely on the psychologists “gut feel” for a suicide attempt, or would you rely on the computer’s calculated logic? Or maybe both?
Note: This site provides NO information on our value investing ETFs or our momentum investing ETFs. Please refer to this site.
Join thousands of other readers and subscribe to our blog.
Please remember that past performance is not an indicator of future results. Please read our full disclosures. The views and opinions expressed herein are those of the author and do not necessarily reflect the views of Alpha Architect, its affiliates or its employees. This material has been provided to you solely for information and educational purposes and does not constitute an offer or solicitation of an offer or any advice or recommendation to purchase any securities or other financial instruments and may not be construed as such. The factual information set forth herein has been obtained or derived from sources believed by the author and Alpha Architect to be reliable but it is not necessarily all-inclusive and is not guaranteed as to its accuracy and is not to be regarded as a representation or warranty, express or implied, as to the information’s accuracy or completeness, nor should the attached information serve as the basis of any investment decision. No part of this material may be reproduced in any form, or referred to in any other publication, without express written permission from Alpha Architect.
Definitions of common statistics used in our analysis are available here (towards the bottom)