Bariatric surgery performance: A predictive informatics case study

Authors:
Christophe Giraud-Carrier;Burdette Pixton;Roberto A. Rocha
Affiliations:
(Correspd. Tel.: +1 801 422 3027/ Fax: +1 801 422 0169/ E-mail: cgc@cs.byu.edu) Department of Computer Science, Brigham Young University, Provo, UT 84602, USA;RemedyMD, Inc., 9350 South 150 East, Suite 850, Sandy, UT 84070, USA;RemedyMD, Inc., 9350 South 150 East, Suite 850, Sandy, UT 84070, USA
Venue:
Intelligent Data Analysis
Year:
2009

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Abstract

The systematic collection and organization of routine medical care data, together with data mining techniques, offer a rich environment for valuable, large-scale observational studies. We report on one such study in the context of bariatric surgery, where we build predictive models for surgical procedure selection and overall success of surgery. We suggest that observational studies supported by predictive informatics may usefully complement classical clinical trials in medical research.