Comparison of Machine Learning Techniques for Mortality Prediction in a Prospective Cohort of Older Adults.

ABSTRACT: As global demographics change, ageing is a global phenomenon which is increasingly of interest in our modern and rapidly changing society. Thus, the application of proper prognostic indices in clinical decisions regarding mortality prediction has assumed a significant importance for personalized risk management (i.e., identifying patients who are at high or low risk of death) and to help ensure effective healthcare services to patients. Consequently, prognostic modelling expressed as all-cause mortality prediction is an important step for effective patient management. Machine learning has the potential to transform prognostic modelling. In this paper, results on the development of machine learning models for all-cause mortality prediction in a cohort of healthy older adults are reported. T

SUBMITTER: Tedesco S 

PROVIDER: S-EPMC8657506 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature