Use of Artificial Intelligence in the Identification and Diagnosis of Frailty Syndrome in Older Adults: Scoping Review.

Journal: Journal of medical Internet research
PMID: 37862082

Abstract

BACKGROUND: Frailty syndrome (FS) is one of the most common noncommunicable diseases, which is associated with lower physical and mental capacities in older adults. FS diagnosis is mostly focused on biological variables; however, it is likely that this diagnosis could fail owing to the high biological variability in this syndrome. Therefore, artificial intelligence (AI) could be a potential strategy to identify and diagnose this complex and multifactorial geriatric syndrome.

Authors

  • Daniel Velazquez-Diaz
    ExPhy Research Group, Department of Physical Education, Faculty of Education Sciences, University of Cadiz, Cádiz, Spain.
  • Juan E Arco
    Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain.
  • Andrés Ortiz
    1 Communications Engineering Department, University of Málaga, 29071/Málaga, Spain.
  • Verónica Pérez-Cabezas
    MOVE-IT Research Group, Department of Nursing and Physiotherapy, Faculty of Health Sciences, University of Cádiz, Cádiz, Spain.
  • David Lucena-Anton
    Biomedical Research and Innovation Institute of Cádiz, Cádiz, Spain.
  • Jose A Moral-Munoz
    Biomedical Research and Innovation Institute of Cádiz, Cádiz, Spain.
  • Alejandro Galán-Mercant
    MOVE-IT Research Group, Department of Nursing and Physiotherapy, Faculty of Health Sciences, University of Cádiz, Cádiz, Spain.

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