Conventional regression analysis and machine learning in prediction of anastomotic leakage and pulmonary complications after esophagogastric cancer surgery

BACKGROUND AND OBJECTIVES: With the current advanced data‐driven approach to health care, machine learning is gaining more interest. The current study investigates the added value of machine learning to linear regression in predicting anastomotic leakage and pulmonary complications after upper gastr...

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Detalles Bibliográficos
Autores principales: van Kooten, Robert T., Bahadoer, Renu R., ter Buurkes de Vries, Bouwdewijn, Wouters, Michel W. J. M., Tollenaar, Rob A. E. M., Hartgrink, Henk H., Putter, Hein, Dikken, Johan L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Gastric and Ugi
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9544929/
https://www.ncbi.nlm.nih.gov/pubmed/35503455
http://dx.doi.org/10.1002/jso.26910

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9544929/
https://www.ncbi.nlm.nih.gov/pubmed/35503455
http://dx.doi.org/10.1002/jso.26910

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