AIMC Topic: Frail Elderly
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The predictive role of identifying frailty in assessing the need for palliative care in the elderly: the application of machine learning algorithm.
Journal of health, population, and nutrition
Apr 23, 2025
BACKGROUND: Palliative care is a key component of integrated care to improve care quality and reduce hospitalization costs for patients with chronic obstructive pulmonary disease (COPD). This study aims to use machine learning algorithms to create an...
Frailty identification using a sensor-based upper-extremity function test: a deep learning approach.
Scientific reports
Apr 22, 2025
The global increase in the older adult population highlights the need for effective frailty assessment, a condition linked to adverse health outcomes such as hospitalization and mortality. Existing frailty assessment tools, like the Fried phenotype a...
Machine Learning Models for Frailty Classification of Older Adults in Northern Thailand: Model Development and Validation Study.
JMIR aging
Apr 2, 2025
BACKGROUND: Frailty is defined as a clinical state of increased vulnerability due to the age-associated decline of an individual's physical function resulting in increased morbidity and mortality when exposed to acute stressors. Early identification ...
Risk prediction models for frailty in older adults: A systematic review and critical appraisal.
International journal of nursing studies
Mar 21, 2025
BACKGROUND: Frailty can lead to increased adverse health outcomes in older adults. Risk prediction models for frailty have benefits in guiding the prevention. Studies have increasingly focused on the development of risk prediction models for frailty ...
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...
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...
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 ...
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