Machine learning methods to discover hidden patterns in well-being and resilience for healthy aging.

Journal: Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
PMID: 39248511

Abstract

BACKGROUND: A whole person approach to healthy aging can provide insight into social factors that may be critical. Digital technologies, such as mobile health (mHealth) applications, hold promise to provide novel insights for healthy aging and the ability to collect data between clinical care visits. Machine learning/artificial intelligence methods have the potential to uncover insights into healthy aging. Nurses and nurse informaticians have a unique lens to shape the future use of this technology.

Authors

  • Robin R Austin
    School of Nursing, University of Minnesota, Minneapolis, Minnesota, USA.
  • Ratchada Jantraporn
    School of Nursing, University of Minnesota, Minneapolis, Minnesota, USA.
  • Martin Michalowski
    School of Nursing, University of Minnesota-Twin Cities, Minneapolis, MN 55455, USA.
  • Jenna Marquard
    School of Nursing, University of Minnesota, Minneapolis, Minnesota, USA.

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