A comparison of machine learning models and Cox proportional hazards models regarding their ability to predict the risk of gastrointestinal cancer based on metabolic syndrome and its components

BACKGROUND: Little is known about applying machine learning (ML) techniques to identify the important variables contributing to the occurrence of gastrointestinal (GI) cancer in epidemiological studies. We aimed to compare different ML models to a Cox proportional hazards (CPH) model regarding their...

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Detalles Bibliográficos
Autores principales: Tran, Tao Thi, Lee, Jeonghee, Gunathilake, Madhawa, Kim, Junetae, Kim, Sun-Young, Cho, Hyunsoon, Kim, Jeongseon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018751/
https://www.ncbi.nlm.nih.gov/pubmed/36937438
http://dx.doi.org/10.3389/fonc.2023.1049787

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018751/
https://www.ncbi.nlm.nih.gov/pubmed/36937438
http://dx.doi.org/10.3389/fonc.2023.1049787

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