Large scale prediction of sick leave duration with nonlinear survival analysis algorithms

作者：

Highlights：

• Modelling of Patient sick leaves at large scale from historical data.

• Studying non-linear survival analysis methods for decision support systems.

• Analysing attribute relevance extracted from decision trees survival models.

• Building a Decision Support System for sick leaves management.

摘要

•Modelling of Patient sick leaves at large scale from historical data.•Studying non-linear survival analysis methods for decision support systems.•Analysing attribute relevance extracted from decision trees survival models.•Building a Decision Support System for sick leaves management.

论文关键词：Sick leave prediction,Survival analysis,Machine learning,Decision support systems,AI in medicine

论文评审过程：Received 1 April 2021, Revised 18 January 2022, Accepted 24 February 2022, Available online 9 March 2022, Version of Record 15 March 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116760