Postoperative bleeding risk prediction for patients undergoing colorectal surgery.

ABSTRACT:

Background

There is limited consensus regarding risk factors for postoperative bleeding. The objective of this work was to investigate the capability of machine learning techniques in combination with practice-based longitudinal electronic medical record data for identifying potential new risk factors for postoperative bleeding and predicting patients at high risk of postoperative bleeding.

Methods

A retrospective study was conducted for patients who underwent colorectal surgery 1998-2015 at a single tertiary referral center. Various predictors were extracted from electronic medical record. The outcome of interest was the occurrence of postoperative bleeding within 7 days of surgery. Logistic regression and gradient boosting machine models were trained. Area under the receiv

SUBMITTER: Chen D 

PROVIDER: S-EPMC6263850 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature