Bariatric surgery performance: A predictive informatics case study

Article type: Research Article

Authors: Giraud-Carrier, Christophe^{a; *} | Pixton, Burdette^b | Rocha, Roberto A.^b

Affiliations: [a] Department of Computer Science, Brigham Young University, Provo, UT 84602, USA | [b] RemedyMD, Inc., 9350 South 150 East, Suite 850, Sandy, UT 84070, USA

Correspondence: [*] Corresponding author. Tel.: +1 801 422 3027; Fax: +1 801 422 0169; E-mail: cgc@cs.byu.edu.

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.

Keywords: Data Mining, Bariatric Surgery, Predictive Informatics

DOI: 10.3233/IDA-2009-0391

Journal: Intelligent Data Analysis, vol. 13, no. 5, pp. 741-754, 2009