Benchmarking in Congenital Heart Surgery Using Machine Learning-Derived Optimal Classification Trees

Benchmarking in Congenital Heart Surgery Using Machine Learning-Derived Optimal Classification Trees

<jats:p> Background: We have previously shown that the machine learning methodology of optimal classification trees (OCTs) can accurately predict risk after congenital heart surgery (CHS). We have now applied this methodology to define benchmarking standards after CHS, permitting case-adjusted...

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Bibliographic Details
Main Authors: Bertsimas, Dimitris, Zhuo, Daisy, Levine, Jordan, Dunn, Jack, Tobota, Zdzislaw, Maruszewski, Bohdan, Fragata, Jose, Sarris, George E
Other Authors: Massachusetts Institute of Technology. Operations Research Center
Format: Article
Language:English
Published: SAGE Publications 2022
Online Access:https://hdl.handle.net/1721.1/144102

Internet

https://hdl.handle.net/1721.1/144102

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