EconPapers    
Economics at your fingertips  
 

Predicting Mortality after Coronary Artery Bypass Surgery

Jack V. Tu, Milton C. Weinstein, Barbara J. McNeil and C. David Naylor

Medical Decision Making, 1998, vol. 18, issue 2, 229-235

Abstract: Objective. To compare the abilities of artificial neural network and logistic regression models to predict the risk of in-hospital mortality after coronary artery bypass graft (CABG) surgery. Methods. Neural network and logistic regression models were developed using a training set of 4,782 patients undergoing CABG surgery in Ontario, Canada, in 1991, and they were validated in two test sets of 5,309 and 5,517 patients having CABG surgery in 1992 and 1993, respectively. Results. The probabilities predicted from a fully trained neural network were similar to those of a “saturated†regression model, with both models detecting all possible interactions in the training set and validating poorly in the two test sets. A second neural network was developed by cross-validating a network against a new set of data and terminating network training early to create a more generalizable model. A simple “main effects†regression model without any interaction terms was also developed. Both of these models validated well, with areas under the receiver operating characteristic curves of 0.78 and 0.77 (p > 0.10) in the 1993 test set. The predictions from the two models were very highly correlated (r = 0.95). Conclusions. Artificial neural networks and logistic regression models learn similar relationships between patient characteristics and mortality after CABG surgery.

Keywords: cardiac surgery; mortality; neural networks; logistic regression; ROC curves (search for similar items in EconPapers)
Date: 1998
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X9801800212 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:18:y:1998:i:2:p:229-235

DOI: 10.1177/0272989X9801800212

Access Statistics for this article

More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().

 
Page updated 2025-03-19
Handle: RePEc:sae:medema:v:18:y:1998:i:2:p:229-235