A novel explainable machine learning-based healthy ageing scale.

ABSTRACT:

Background

Ageing is one of the most important challenges in our society. Evaluating how one is ageing is important in many aspects, from giving personalized recommendations to providing insight for long-term care eligibility. Machine learning can be utilized for that purpose, however, user reservations towards "black-box" predictions call for increased transparency and explainability of results. This study aimed to explore the potential of developing a machine learning-based healthy ageing scale that provides explainable results that could be trusted and understood by informal carers.

Methods

In this study, we used data from 696 older adults collected via personal field interviews as part of independent research. Explanatory factor analysis was used to find candidate health

SUBMITTER: Gasperlin Stepancic K 

PROVIDER: S-EPMC11520378 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature