Utilizing Machine Learning Methods for Preoperative Prediction of Postsurgical Mortality and Intensive Care Unit Admission

OBJECTIVE: To compare the performance of machine learning models against the traditionally derived Combined Assessment of Risk Encountered in Surgery (CARES) model and the American Society of Anaesthesiologists-Physical Status (ASA-PS) in the prediction of 30-day postsurgical mortality and need for...

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Detalles Bibliográficos
Autores principales: Chiew, Calvin J., Liu, Nan, Wong, Ting Hway, Sim, Yilin E., Abdullah, Hairil R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2020
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668340/
https://www.ncbi.nlm.nih.gov/pubmed/30973386
http://dx.doi.org/10.1097/SLA.0000000000003297

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668340/
https://www.ncbi.nlm.nih.gov/pubmed/30973386
http://dx.doi.org/10.1097/SLA.0000000000003297

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