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Machine learning approaches for frailty detection, prediction and classification in elderly people: A systematic
Matteo Leghissa1, Álvaro Carrera1, Carlos A Iglesias1
1Universidad Politécnica de Madrid, Av. Complutense, 30, 28040, Madrid, Spain.
International Journal of Medical Informatics
|August 16, 2023
Summary
Machine Learning models can aid in detecting and predicting frailty in older adults. Further research is needed for a universal definition and improved Explainability in healthcare applications.
Area of Science:
- Gerontology
- Artificial Intelligence
- Biomedical Informatics
Background:
- Frailty is an age-related syndrome with increasing prevalence and healthcare costs.
- Early detection and prediction of frailty are crucial for improving health outcomes in older adults.
- Machine Learning (ML) offers potential for decision support tools in frailty assessment.
Conclusions:
- A universal quantitative definition of frailty is needed.
- Collaboration between medical professionals and data scientists is essential.
- Explainability in ML models for healthcare requires further investigation.
