Geriatrics

Leveraging Naturalistic Driving Digital Biomarkers for Early Mild Cognitive Impairment Detection: Deep Learning Strategies.

BACKGROUND: Alzheimer disease and related dementias are increasing worldwide, with early detection during the mild cognitive impairment (MCI) stage critical for timely intervention. Driving behavior, which reflects everyday cognitive functioning, has emerged as a promising, noninvasive, and inexpensive digital biomarker when paired with machine learning. However, prior research has often relied on...

Possible cross‑talk between sarcopenia and obstructive sleep apnea revealed by WGCNA analysis and machine learning.

BACKGROUND: Emerging evidence suggests a potential link between obstructive sleep apnea (OSA) and sarcopenia. OSA-induced hypoxia and sleep disturbances may promote the loss of muscle mass, thereby increasing the risk of sarcopenia. This study employed bioinformatics approaches to identify key diagnostic candidate genes underlying the interaction between OSA and sarcopenia. METHODS: In this study,...

Can health technologies be "care optimizers"? A normative evaluation of digital health technologies in light of postphenomenological reflections.

The integration of new technologies such as artificial intelligence (AI) into healthcare has initiated profound changes in clinical practice, reshapin...

Derivation of machine learning brain aging biomarkers for a set of forty thousand functional connectomes.

Various Magnetic Resonance Imaging modalities were developed to explore the brain. Among them, functional MRI is of key importance for studying brain ...

Machine learning model integrating oral microbiota and clinical features for predicting osteoporosis and bone loss in high-altitude populations.

Artificial Intelligence-Enabled Electrocardiographic Detection of Severe Aortic Stenosis Leading to Transcatheter Aortic Valve Replacement.

BACKGROUND: EchoNext is an artificial intelligence (artificial intelligence)-enabled electrocardiographic (ECG) model validated to detect unrecognized...

MRI In Vivo Detection of Amyloid-β Protein Deposition in Different Brain Regions of Patients with AD and MCI.

To investigate a non-invasive magnetic resonance imaging (MRI)-based method for detecting amyloid-β (Aβ) protein deposition in different brain regions...

Women's reproductive factors predict local brain aging profiles mapped using deep neural networks.

Deep neural networks (DNNs) trained on magnetic resonance images can estimate global brain age (GBA), which reflects women's neurological disease risk...

Evaluating the Use of Generative AI Videos for Health Self-Management of Older Adults: Mixed Methods Study.

BACKGROUND: Aging is a pressing global issue, and older adults need to build up their knowledge to manage their health. Insufficient self-efficacy and...

Speech-to-Speech Voice-Cloning Care (SVCC) for improving ICU-acquired anxiety for critically ill patients in a tertiary hospital in Beijing, China: protocol of a randomised, controlled trial.

INTRODUCTION: Intensive care unit (ICU) visiting restrictions in hospitals, implemented due to infection control and other factors, limited contact be...

Integrating ensemble machine-learning and fibril docking to discover potent, novel triazole-naphthalene tau-aggregation inhibitors.

Tau-protein aggregation is a central pathological feature of Alzheimer's disease, so blocking fibril growth is an attractive therapeutic goal. We cura...

Bone Mineral Density of Spine Patients with CT Hounsfield Units and AI Segmentation: A Contemporary Review.

It is widely accepted that bone mineral density affects outcomes for spinal arthrodesis surgeries. Traditional techniques such as dual-energy X-ray ab...

Development of an interpretable machine learning model-based online tool for risk identification of anxiety symptoms in Chinese older adults.

BACKGROUND: As the population aging process has accelerated, anxiety symptoms (AS) among older adults have become a critical concern. In addition to d...

Integration of multi-omics and machine learning to reveal the anti-osteoporosis effects of Hederagenin by inhibiting lipid peroxidation via the GPX4/p-STAT1/PTGS2 axis.

Osteoporosis (OP) is a multifactorial disease, leading to abnormal bone remodeling, requiring targeted therapeutic interventions. This study investiga...

AI-Driven Internet of Things (IoT) dataset for remote health monitoring and fall detection in elderly people.

Many older adults live with one or more chronic conditions that require ongoing monitoring. At the same time, the aging population continues to grow, ...

The role of ionotropic glutamate receptors in Alzheimer's disease: A scientometric analysis.

BackgroundAlzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by amyloid-β plaques, neurofibrillary tangles, and synapt...

Deep learning ensemble models for CT-based differentiation of malignant and benign sacral bone tumors: development and evaluation.

OBJECTIVE: Radiologists often face challenges in differentiating benign from malignant sacral bone lesions due to their similar imaging characteristic...

A CNN-transformer fusion for EEG-based discrimination of Alzheimer's and frontotemporal dementia.

Dementia is a progressive neurodegenerative disorder that severely impacts cognitive functions and daily living, especially in aging populations. Amon...

METRON: Metabolic Dynamic Perception Kolmogorov-Arnold Network for Biological Age Estimation.

Biological age provides a more direct reflection of physiological status than chronological age, serving as a vital measure to evaluate health risks a...

Enabling digital multifactorial risk assessment in primary care: an umbrella review and recommendations for design and implementation.

OBJECTIVES: To develop recommendations to inform development and integration of predictive digital health and artificial intelligence tools in primary...