Geriatrics

Deep learning models identify brain changes during the progression of Alzheimer's disease.

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder whose progression is closely ...

Development and Validation of a Frailty Risk Prediction Model for Preoperative Non-Small-Cell Lung Cancer Patients: A Cross-Sectional Study.

PURPOSE: Frailty is increasingly recognized as a predictor of poor surgical outcomes, yet its preope...

Advancements in ex vivo bone biomechanics: multimodal technologies and their integration with artificial intelligence.

Bone biomechanics is essential for understanding how bone structure, composition, and mechanical fun...

Brain age prediction in a multiethnic Asian population: A comparison of machine learning algorithms and their application for early-stage cognitive impairment diagnosis.

BackgroundNeuroimaging-derived brain age is a promising biomarker of early neurodegeneration, but me...

Using participatory action research to develop an artificial intelligence-augmented, peer-driven, case-based, and simulation-enhanced curriculum for emergency medicine residents.

This work describes the use of participatory action research to develop an artificial intelligence (...

Fine-Tuned Large Language Models for Generating Multiple-Choice Questions in Anesthesiology: Psychometric Comparison With Faculty-Written Items.

BACKGROUND: Multiple-choice examinations (MCQs) are widely used in medical education to ensure stand...

Neuropathologic basis of quantitative susceptibility mapping in the substantia nigra: contributions of tau, pigmented neurons, and iron.

Quantitative susceptibility mapping (QSM) on MRI quantifies tissue magnetic susceptibility, which in...

Longitudinal brain-age predictions comprising long-duration spaceflight missions.

Our study investigates the effects of long-duration spaceflight on brain aging in spacefarers using ...

In Situ Evaluation of Virtual Reality Simulation Usability and Learning in Nursing.

BACKGROUND: Virtual reality is increasingly applied in nursing education to enhance student readines...

Exploration of an interpretable machine learning-based screening manner for low muscle mass among Chinese community-dwelling older adults using routine physical examination information.

BACKGROUND: With the accelerating aging of the global population, muscle health issue occurs commonl...

Primary Care Physician Perspectives on Artificial Intelligence for Dementia Screening: A Qualitative Study.

BACKGROUND: Automated approaches to cognitive impairment screening may soon achieve sufficient level...

Heterophily-Aware Spectral GCN for Population-Level Brain Disorder Prediction.

Integrating resting-state functional magnetic resonance imaging (rs-fMRI) and phenotypic data is a p...

DRfold2 is a deep learning-based tool that enables efficient and accurate RNA structure prediction.

RNA structures are essential for understanding their biological functions and developing RNA-targete...

Assessing the Impact of Sociodemographic Factors on Artificial Intelligence Models in Predicting Dementia: Retrospective Cohort Study.

BACKGROUND: Artificial intelligence (AI) is increasingly applied to health care, yet concerns about ...

Early diagnosis of Alzheimer's Disease: Graph theoretical analysis of cerebellar network features based on 18F-AV45 PET.

Pathological and neuroimaging changes in the cerebellum of Alzheimer's disease (AD) patients have be...

Vascular Age: A narrative review of assessment methods, clinical applications, and future directions.

Cardiovascular disease (CVD) is the leading cause of death and disability globally, highlighting the...

Exploring estrogen synthesis and metabolism related markers and immune dynamics in osteoporosis-insights from single-cell RNA sequencing and Mendelian randomization.

BACKGROUND: Osteoporosis (OP) is characterized by decreased bone mineral density and an increased fr...

Machine learning and artificial intelligence for delirium prediction with Electronic Health Records (EHR): a scoping review.

3D deep-learning radiomics from MR-T2WI for predicting placenta accreta spectrum disorders: A multicenter study.

OBJECTIVE: To develop a three-dimensional (3D) deep-learning radiomics from magnetic resonance-T2-we...

Computational Drug Repurposing for Alzheimer's Disease via Sheaf Theoretic Population-Scale Analysis of snRNA-Seq Data.

Single-cell and single-nucleus RNA sequencing are used to reveal heterogeneity in cells, showing a g...

Comprehensive multimodal prediction of Alzheimer's disease.

Alzheimer's disease (AD) classification using machine learning has increasingly relied on multimodal...