Improved Prediction of Surgical-Site Infection After Colorectal Surgery Using Machine Learning.
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ABSTRACT:
SUBMITTER: Chen KA
PROVIDER: S-EPMC10069984 | biostudies-literature | 2023 Mar
REPOSITORIES: biostudies-literature
Publications
Improved Prediction of Surgical-Site Infection After Colorectal Surgery Using Machine Learning.
Chen Kevin A KA Joisa Chinmaya U CU Stem Jonathan M JM Guillem Jose G JG Gomez Shawn M SM Kapadia Muneera R MR
Diseases of the colon and rectum 20221130 3
<h4>Background</h4>Surgical-site infection is a source of significant morbidity after colorectal surgery. Previous efforts to develop models that predict surgical-site infection have had limited accuracy. Machine learning has shown promise in predicting postoperative outcomes by identifying nonlinear patterns within large data sets.<h4>Objective</h4>This study aimed to seek usage of machine learning to develop a more accurate predictive model for colorectal surgical-site infections.<h4>Design</h ...[more]
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