FRELSA: A dataset for frailty in elderly people originated from ELSA and evaluated through machine learning models
Creating new frailty-annotated datasets of this size is necessary to develop and improve the frailty prediction techniques. We have shown that our dataset can be used to study and test machine learning models to detect and predict frailty. Future work should improve models' architecture and performance, consider explainability, and possibly enrich the dataset with older waves.
Authors
- Carlos Á. Iglesias (ORCID: https://orcid.org/0000-0002-1755-2712)
- M. Leghissa (ORCID: https://orcid.org/0009-0002-0173-720X)
- Álvaro Carrera (ORCID: https://orcid.org/0000-0002-0319-036X)
Institutions
- Universidad Politécnica de Madrid (ES)
Publication Details
- Journal
- International Journal of Medical Informatics
- Published
- 2024-08-19
- DOI
- https://doi.org/10.1016/j.ijmedinf.2024.105603
- Citations
- 3
- Primary Topic
- Frailty in Older Adults
- Type
- article
- Field-Weighted Citation Impact
- 1.03
Funders
- Ministerio de Ciencia, Innovación y Universidades
- European Commission
- Universidad Carlos III de Madrid
- Universidad de Castilla-La Mancha
- Agencia Estatal de Investigación