Dynamic Risk Prediction of 30-Day Mortality in Patients With Advanced Lung Cancer:Comparing Five Machine Learning Approaches

Autor: Charles Vesteghem, Weronika M. Szejniuk, Rasmus F. Brøndum, Ursula G. Falkmer, Chloé-Agathe Azencott, Martin Bøgsted

Publikováno v: Vesteghem, C, Szejniuk, W M, Brøndum, R F, Falkmer, U G, Azencott, C-A & Bøgsted, M 2022, ' Dynamic Risk Prediction of 30-Day Mortality in Patients With Advanced Lung Cancer : Comparing Five Machine Learning Approaches ', JCO Clinical Cancer Informatics, vol. 6, e2200054, pp. e2200054 . https://doi.org/10.1200/CCI.22.00054
Vesteghem, C, Szejniuk, W M, Brøndum, R F, Falkmer, U G, Azencott, C-A & Bøgsted, M 2022, ' Dynamic Risk Prediction of 30-Day Mortality in Patients With Advanced Lung Cancer : Comparing Five Machine Learning Approaches ', JCO Clinical Cancer Informatics, vol. 6, e2200054 . https://doi.org/10.1200/CCI.22.00054

PURPOSE Administering systemic anticancer treatment (SACT) to patients near death can negatively affect their health-related quality of life. Late SACT administrations should be avoided in these cases. Machine learning techniques could be used to bui

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