Development and Validation of a Machine Learning Model to Identify Patients Before Surgery at High Risk for Postoperative Adverse Events

IMPORTANCE: Identifying patients at high risk of adverse outcomes prior to surgery may allow for interventions associated with improved postoperative outcomes; however, few tools exist for automated prediction. OBJECTIVE: To evaluate the accuracy of an automated machine-learning model in the identif...

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Detalles Bibliográficos
Autores principales: Mahajan, Aman, Esper, Stephen, Oo, Thien Htay, McKibben, Jeffery, Garver, Michael, Artman, Jamie, Klahre, Cynthia, Ryan, John, Sadhasivam, Senthilkumar, Holder-Murray, Jennifer, Marroquin, Oscar C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2023
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329211/
https://www.ncbi.nlm.nih.gov/pubmed/37418262
http://dx.doi.org/10.1001/jamanetworkopen.2023.22285

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10329211/
https://www.ncbi.nlm.nih.gov/pubmed/37418262
http://dx.doi.org/10.1001/jamanetworkopen.2023.22285

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