Geriatrics

Integrating machine learning and SHAP analysis to identify the risk of cognitive frailty in older adults with chronic heart failure.

BACKGROUND: Accurately identifying older adults with chronic heart failure (CHF) at high risk of cognitive frailty is crucial for timely preventive interventions, yet current approaches to detect this risk are under-researched. This study aimed to construct and test machine learning models to identify cognitive frailty risk in older CHF patients. METHODS: This cross-sectional study continuously en...

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 function interact in healthy and diseased states. Conventional approaches such as mechanical testing, micro computed tomography, and histology provide valuable information but cannot fully capture the multiscale heterogeneity that governs bone strength and fragility. This review summarizes recent progr...

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 methodological variation in machine learning (ML) al...

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 (AI)-augmented, peer-driven, case-based, and simula...

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 standardized and objective assessment. Developing high-...

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 increases with iron accumulation, myelin loss, and n...

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

Our study investigates the effects of long-duration spaceflight on brain aging in spacefarers using structural MRI and machine learning models. Pre-, ...

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

BACKGROUND: Virtual reality is increasingly applied in nursing education to enhance student readiness for patient care. This study evaluated the effec...

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 commonly as an age-related process in older people. The c...

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

BACKGROUND: Automated approaches to cognitive impairment screening may soon achieve sufficient levels of accuracy for clinical implementation but they...

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

Integrating resting-state functional magnetic resonance imaging (rs-fMRI) and phenotypic data is a promising way to build a comprehensive population g...

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-targeted therapeutics. However, accurate RNA structure pr...

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 fairness persist, particularly in relation to soci...

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 been well documented. However, the changes in cerebe...

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 importance of effective risk assessment and early...

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 fracture risk, often due to declining sex hormone le...

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-weighted imaging (T2WI) for predicting the risk of p...

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 growing potential for precision and personalized me...

Comprehensive multimodal prediction of Alzheimer's disease.

Alzheimer's disease (AD) classification using machine learning has increasingly relied on multimodal inputs such as Magnetic Resonance Imaging (MRI), ...