AIMC Topic: Frailty
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Development and Validation of a Machine Learning Method Using Vocal Biomarkers for Identifying Frailty in Community-Dwelling Older Adults: Cross-Sectional Study.
JMIR medical informatics
Jan 16, 2025
BACKGROUND: The two most commonly used methods to identify frailty are the frailty phenotype and the frailty index. However, both methods have limitations in clinical application. In addition, methods for measuring frailty have not yet been standardi...
Predicting admission for fall-related injuries in older adults using artificial intelligence: A proof-of-concept study.
Geriatrics & gerontology international
Jan 12, 2025
AIM: Pre-injury frailty has been investigated as a tool to predict outcomes of older trauma patients. Using artificial intelligence principles of machine learning, we aimed to identify a "signature" (combination of clinical variables) that could pred...
Frailty Modeling Using Machine Learning Methodologies: A Systematic Review With Discussions on Outstanding Questions.
IEEE journal of biomedical and health informatics
Jan 7, 2025
Studying frailty is crucial for enhancing the health and quality of life among older adults, refining healthcare delivery methods, and tackling the obstacles linked to an aging demographic. Approaches to frailty modeling often utilise simple analytic...
Predicting grip strength-related frailty in middle-aged and older Chinese adults using interpretable machine learning models: a prospective cohort study.
Frontiers in public health
Dec 17, 2024
INTRODUCTION: Frailty is an emerging global health burden, and there is no consensus on the precise prediction of frailty. We aimed to explore the association between grip strength and frailty and interpret the optimal machine learning (ML) model usi...
Artificial intelligence driven clustering of blood pressure profiles reveals frailty in orthostatic hypertension.
Experimental physiology
Nov 11, 2024
Gravity, an invisible but constant force , challenges the regulation of blood pressure when transitioning between postures. As physiological reserve diminishes with age, individuals grow more susceptible to such stressors over time, risking inadequat...
Predicting frailty in older patients with chronic pain using explainable machine learning: A cross-sectional study.
Geriatric nursing (New York, N.Y.)
Nov 8, 2024
Frailty is common among older adults with chronic pain, and early identification is crucial in preventing adverse outcomes like falls, disability, and dementia. However, effective tools for identifying frailty in this population remain limited. This ...
Advances of artificial intelligence in predicting frailty using real-world data: A scoping review.
Ageing research reviews
Oct 5, 2024
BACKGROUND: Frailty assessment is imperative for tailoring healthcare interventions for older adults, but its implementation remains challenging due to the effort and time needed. The advances of artificial intelligence (AI) and natural language proc...
The application of machine learning for identifying frailty in older patients during hospital admission.
BMC medical informatics and decision making
Sep 27, 2024
BACKGROUND: Early identification of frail patients and early interventional treatment can minimize the frailty-related medical burden. This study investigated the use of machine learning (ML) to detect frailty in hospitalized older adults with acute ...
FRELSA: A dataset for frailty in elderly people originated from ELSA and evaluated through machine learning models.
International journal of medical informatics
Aug 19, 2024
BACKGROUND: Frailty is an age-related syndrome characterized by loss of strength and exhaustion and associated with multi-morbidity. Early detection and prediction of the appearance of frailty could help older people age better and prevent them from ...
Development and Validation of Prediction Models for Incident Reversible Cognitive Frailty Based on Social-Ecological Predictors Using Generalized Linear Mixed Model and Machine Learning Algorithms: A Prospective Cohort Study.
Journal of applied gerontology : the official journal of the Southern Gerontological Society
Aug 6, 2024
This study aimed to develop and validate prediction models for incident reversible cognitive frailty (RCF) based on social-ecological predictors. Older adults aged ≥60 years from China Health and Retirement Longitudinal Study (CHARLS) 2011-2013 surve...
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