Geriatrics

SuperLearner approach for predicting imminent risk of fracture in older Chinese patients with newly diagnosed osteoporosis based on their routine blood test markers.

Fall Detection Based on Computer Vision: A Systematic Mapping Study.

Falls are a leading cause of injury and mortality among older adults, motivating growing interest in video-based computer vision (CV) fall detection systems. This study presents a systematic mapping of vision-based fall detection in video, synthesizing evidence from 433 primary studies published through 2025 and retrieved from five databases using explicit eligibility criteria and independent dual...

Exploring Information Access in Aging Populations and Those With Dementia and Mild Cognitive Impairment in the United Kingdom: Survey and Focus Group Study.

BACKGROUND: With the growing aging population, technology that supports independent living is increasingly important. Web search systems are well esta...

Engaging Hospital Staff to Identify Levers for Adoption of Clinical Decision Support: Protocol for a Single-Site Case Study Using System Dynamics Group Model Building.

BACKGROUND: Clinical decision support (CDS) tools that provide patient-specific and evidence-based information to clinicians and care managers regardi...

Establishment and validation of an Alzheimer's disease diagnostic model on the basis of exhaled volatile organic compound characteristics.

Exhaled volatile organic compounds (VOCs) have been investigated in some diseases, including cognitive impairment, in pilot studies. The present study...

The effect of robot-based interventions on depression in older adults with cognitive impairment: A systematic review and meta-analysis.

OBJECTIVE: To assess the effectiveness of robot-based interventions in improving depressive symptoms among older adults with cognitive impairment, and...

The utility of Speech and Language analytics for screening Alzheimer's Disease.

BACKGROUND: Effective screening and cohort enrichment remain major challenges in clinical trials for Alzheimer's disease (AD), where traditional diagn...

SSiamese Capsule Network (SNNCap) : Cognitive Analysis for Alzheimer's Disease Classification from MRI Data.

Alzheimer's Disease (AD) detection is essential for timely treatment and better patient care. Magnetic Resonance Imaging (MRI) is a technique in which...

League of Radiologists-an End-to-End AI Framework for Scalable and Gamified Radiology Education: A Pilot Implementation in Chest Radiography.

Traditional radiology education is constrained by a restricted apprenticeship model and a scarcity of datasets structured for building artificial inte...

Literature-derived serum miRNA signatures associated with cognitive decline in Alzheimer's disease: integrated analysis and machine learning-based diagnostic modeling.

Development and Validation of a Machine Learning Model for Predicting Postoperative Delirium in Elderly Patients with Hip Fracture: A Retrospective Cohort Study.

Postoperative delirium (POD) is a common and serious complication in elderly hip fracture patients, including those undergoing surgery for femoral nec...

Patient specific optimization and planning of vertebral augmentation in osteoporosis: Finite element and Artificial Intelligence approaches.

BACKGROUND: Osteoporotic Vertebral Compression Fractures (OVCFs) are responsible for significant disability, especially among individuals with low Bon...

Deciphering the molecular network of Trichostatin A in regulating Alzheimer's disease screening of core genes and mechanistic investigation based on multidimensional bioinformatics and molecular simulation.

BACKGROUND: Histone deacetylases (HDACs) regulate neuroprotection; however, Trichostatin A (TSA), an HDAC inhibitor, lacks clear molecular mechanisms ...

CDR-Net: A computerized framework to detect Alzheimer's diseases and mild cognitive impairment.

Alzheimer's disease (AD) and mild cognitive impairment (MCI) are two dementia-related brain illnesses that are prevalent among elders in the twenty-fi...

Predicting future cognitive impairment in preclinical Alzheimer's disease using amyloid PET and MRI: A multisite machine learning study.

Predicting the likelihood of developing Alzheimer's disease (AD) dementia in at-risk individuals is important for the design of and optimal recruitmen...

Deep-learning framework for osteoporosis screening on low-dose X-rays: Addressing image quality variability and cross-ethnic database Heterogeneity.

The AIXA Osteo model architecture (X1AI-Osteo) has undergone internal validation in Taiwan, demonstrating its capability to evaluate osteoporosis and ...

Advancing brain age estimation: normative deviation mapping (NDM) for sensitive detection of pathological aging.

Brain age is a valuable neuroimaging-based biomarker for assessing brain health, typically estimated using machine learning (ML) models. However, ML a...

iPalmT: a new paradigm for palmitoyltransferase discovery via end-to-end deep learning.

Protein S-palmitoylation, a dynamic lipid modification, is essential for protein stability, trafficking, and signaling; dysregulated palmitoyltransfer...

Association of the Dietary Index for Gut Microbiota with site-specific Osteoporosis: Insights from machine learning applied to a national population.

BACKGROUND: The association between the Dietary Index for Gut Microbiota (DI-GM) and site-specific osteoporosis risk remains unclear. METHODS: This st...

SRSF1 as a promising biomarker and key player in the pathogenesis of Alzheimer's disease.

Given the unclear pathogenesis and insidious progression of Alzheimer's disease (AD), the aim of the present study was to identify reliable diagnostic...