AIMC Topic: Aged, 80 and over
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A high-throughput framework for predicting three-dimensional structural-mechanical relationships of human cranial bones using a deep learning-based method.
Journal of the mechanical behavior of biomedical materials
Apr 24, 2025
Cranial bone injuries significantly impact human health, potentially leading to death or permanent disability, and mechanical responses are crucial predictors of cranial damage. Predicting mechanical responses through medical imaging is an efficient ...
Predicting isolated impaired glucose tolerance without oral glucose tolerance test using machine learning in Chinese Han men.
Frontiers in endocrinology
Apr 24, 2025
BACKGROUND: Isolated Impaired Glucose Tolerance (I-IGT) represents a specific prediabetic state that typically requires a standardized oral glucose tolerance test (OGTT) for diagnosis. This study aims to predict glucose tolerance status in Chinese Ha...
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...
Interpretable machine learning model for predicting delirium in patients with sepsis: a study based on the MIMIC data.
BMC infectious diseases
Apr 23, 2025
OBJECTIVE: The aim of this study was to construct interpretable machine learning models to predict the risk of developing delirium in patients with sepsis and to explore the impact of delirium on the 28-day survival rate of patients.
Elucidating predictors of preoperative acute heart failure in older people with hip fractures through machine learning and SHAP analysis: a retrospective cohort study.
BMC geriatrics
Apr 23, 2025
BACKGROUND: Acute heart failure (AHF) has become a significant challenge in older people with hip fractures. Timely identification and assessment of preoperative AHF have become key factors in reducing surgical risks and improving outcomes.
Improved radiological diagnosis of osteoporotic vertebral fragility fractures following UK-wide interventions and re-audit-can this be maintained and translated into clinical practice?
Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
Apr 22, 2025
UNLABELLED: To determine the potential economic, morbidity and mortality impact of improvements in reporting of vertebral fragility fractures (VFFs) following a complete audit cycle. Six percent interval increase in reporting of moderate/severe VFFs ...
Cerebrospinal fluid inflammatory cytokines as prognostic indicators for cognitive decline across Alzheimer's disease spectrum.
Journal of Alzheimer's disease : JAD
Apr 22, 2025
BackgroundNeuroinflammation actively contributes to the pathophysiology of Alzheimer's disease (AD); however, the value of neuroinflammatory biomarkers for disease-staging or predicting disease progression remains unclear.ObjectiveTo investigate diag...
Screening risk factors for the occurrence of wedge effects in intramedullary nail fixation for intertrochanteric fractures in older people via machine learning and constructing a prediction model: a retrospective study.
BMC musculoskeletal disorders
Apr 22, 2025
PURPOSE: The wedge effect (V-effect) is a common complication in intramedullary nailing surgery for intertrochanteric fractures and can significantly affect postoperative outcomes. The purpose of this study was to screen risk factors for the intraope...
Explainable machine learning framework for biomarker discovery by combining biological age and frailty prediction.
Scientific reports
Apr 22, 2025
Biological age (BA) and frailty represent two distinct health measures that offer valuable insights into the aging process. Comparing and analyzing blood-based biomarkers from the machine learning (ML) predictors of BA and frailty helps deepen our un...
The clinical significance of an AI-based assumption model for neurocognitive diseases using a novel dual-task system.
Scientific reports
Apr 22, 2025
Dual-task composed of gait or stepping tasks combined with cognitive tasks has been well-established as valuable tools for detecting neurocognitive disorders such as mild cognitive impairment and early-stage Alzheimer's disease. We previously develop...
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