Comparison of Machine Learning Methods in the Study of Cancer Survivors' Return to Work: An Example of Breast Cancer Survivors with Work-Related Factors in the CONSTANCES Cohort - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Journal of Occupational and Environmental Medicine Année : 2023

Comparison of Machine Learning Methods in the Study of Cancer Survivors' Return to Work: An Example of Breast Cancer Survivors with Work-Related Factors in the CONSTANCES Cohort

Résumé

Machine learning (ML) methods showed a higher accuracy in identifying individuals without cancer who were unable to return to work (RTW) compared to the classical methods (e.g. logistic regression models). We therefore aim to discuss the value of these methods in relation to RTW for cancer survivors.
Fichier non déposé

Dates et versions

hal-04059455 , version 1 (05-04-2023)

Identifiants

Citer

Marie Badreau, Marc Fadel, Yves Roquelaure, Clémence Rapicault, Mélanie Bertin, et al.. Comparison of Machine Learning Methods in the Study of Cancer Survivors' Return to Work: An Example of Breast Cancer Survivors with Work-Related Factors in the CONSTANCES Cohort. Journal of Occupational and Environmental Medicine, 2023, Publish Ahead of Print, ⟨10.1007/s10926-023-10112-8⟩. ⟨hal-04059455⟩
55 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More