On the Reliability of Machine Learning Models for Survival Analysis When Cure Is a Possibility

Ana Ezquerro, Brais Cancela and Ana López-Cheda ()
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Ana Ezquerro: Faculty of Informatics, University of A Coruña, 15071 A Coruña, Spain
Brais Cancela: CITIC, LIDIA Group, Department of Computer Science, University of A Coruña, 15071 A Coruña, Spain
Ana López-Cheda: CITIC, MODES Group, Department of Mathematics, University of A Coruña, 15071 A Coruña, Spain

Mathematics, 2023, vol. 11, issue 19, 1-21

Abstract: In classical survival analysis, it is assumed that all the individuals will experience the event of interest. However, if there is a proportion of subjects who will never experience the event, then a standard survival approach is not appropriate, and cure models should be considered instead. This paper deals with the problem of adapting a machine learning approach for classical survival analysis to a situation when cure (i.e., not suffering the event) is a possibility. Specifically, a brief review of cure models and recent machine learning methodologies is presented, and an adaptation of machine learning approaches to account for cured individuals is introduced. In order to validate the proposed methods, we present an extensive simulation study in which we compare the performance of the adapted machine learning algorithms with existing cure models. The results show the good behavior of the semiparametric or the nonparametric approaches, depending on the simulated scenario. The practical utility of the methodology is showcased through two real-world dataset illustrations. In the first one, the results show the gain of using the nonparametric mixture cure model approach. In the second example, the results show the poor performance of some machine learning methods for small sample sizes.

Keywords: censored data; cure rate; deep learning; mixture cure models; simulation; system reliability (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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