Latest AI and machine learning research in geriatrics for healthcare professionals.
Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by complex molecular alterations across multiple brain regions. In this study, we applied an integrative systems-level framework combining multi-region transcriptomic analysis, protein-protein interaction (PPI) network topology, machine learning-based validation, and in silico approaches to identify robust and ph...
OBJECTIVE: High accuracy in medical classification tasks does not ensure that neural networks reason in ways consistent with clinical or neurobiological understanding. This study examines whether a Vision Transformer (ViT) trained on resting-state EEG infers cognitive impairment through physiologically meaningful mechanisms. APPROACH: A lightweight ViT was trained on multi-center resting-state EEG...
In this study, we developed ML algorithms to predict fragility fractures, considering the occurrence of fractures at different skeletal sites, using t...
The deep penetration of IoT terminals in water systems, healthcare, transportation, and other fields has exacerbated security threats such as cyber-ph...
BACKGROUND: Empirical evidence on how employees across different service domains within a single multi-sector public organization perceive AI adoption...
BACKGROUND: The rising co-occurrence of cardiometabolic diseases and musculoskeletal degeneration poses a critical challenge to healthy aging, yet the...
OBJECTIVES: This study aims to provide a comprehensive bibliometric mapping of the scientific evolution and research trends of fractal analysis (FA) i...
Aging is a complex biological process characterized by progressive functional decline, driving the incidence of age-related diseases such as neurodege...
Quantum machine learning on noisy intermediate-scale quantum (NISQ) devices often suffers from noise sensitivity, small-data overfitting, and miscalib...
In the intensive care unit (ICU), monitoring sedation levels is crucial. Clinicians often rely on intermittent behavioral scales like the Richmond Agi...
Microglial cells are key players in maintaining brain homeostasis and responding to pathological conditions. Their multifaceted roles in health and di...
OBJECTIVE: Accurate estimation of skeletal muscle mass is a key component in the screening for sarcopenia. Anthropometric parameters provide a non-inv...
BACKGROUND: Sarcopenic obesity (SO) is closely associated with mild cognitive impairment (MCI). However, traditional body composition-based diagnostic...
Evaluation of body composition (BC) is a set of biomarkers, including fat, muscle and bone, that allows the quantification of an individual's composit...
Delirium involves neurotransmitter imbalances and disrupted neural networks. Although lacosamide may theoretically treat delirium by reducing neuronal...
Current Alzheimer's disease therapies offer limited efficacy and are often accompanied by significant side effects, underscoring the urgent need for n...
OBJECTIVE: To develop an artificial intelligence (AI)-aided dual-task gait test model for scalable, high-throughput cognitive impairment screening. DE...
BackgroundAlthough studies have explored tea and coffee in relation to Alzheimer's disease, no century-scale analysis has jointly examined both within...
Exosomes have emerged as critical mediators of intercellular and inter-organ communication in bone biology. Secreted by bone-resident cells such as os...
The determination of paper aging is crucial for forensic document examination, enabling the identification of temporal origin in forgery or fraud case...