CareLit Fachartikel
Predicting risk of falling in older adults using supervised machine learning: a comparative analysis of model performance
Çekok, F.K.; Alcan, V. · Zeitschrift für Gerontologie und Geriatrie · 2025 · Heft 10 · S. 1 bis 7
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568370
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Jahr
2025
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Zusammenfassung
IntroductionFalls among older adults are a significant global health concern, often resulting in severe injuries, loss of independence and increased healthcare costs [1]. With the aging population rising, the burden of fall-related morbidity and mortality continues to increase, necessitating effective prevention strategies [2]. Risk of falling is multifactorial, influenced by age-related physiological decline, impaired balance, gait disturbances, muscle weakness, cognitive impairment and chronic health conditions [3]. Early and accurate fall risk assessment is essential for timely intervention, improved patient…
Schlagworte
Sturzrisiko
ältere Erwachsene
maschinelles Lernen
Risikobewertung
Prävention
Gesundheitskosten
Accidental Falls
Aged
Machine Learning
Risk Assessment
Health Care Costs
Cognitive Dysfunction
Zeitschrift für Gerontologie und Geriatrie
