Geriatrics

Latest AI and machine learning research in geriatrics for healthcare professionals.

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Showing 3718-3738 of 8,132 articles
ARCHE: Autoregressive Residual Compression with Hyperprior and Excitation

Recent progress in learning-based image compression has demonstrated that end-to-end optimization ca...

Can Parents and Patients Understand Myopia Using Large Language Model-Based Chatbots?

Purpose: This study aimed to compare the reliability of myopia-related information from AI chatbots ...

Transformer-Based Multi-Region Segmentation and Radiomic Analysis of HR-pQCT Imaging

Osteoporosis is a skeletal disease typically diagnosed using dual-energy X-ray absorptiometry (DXA),...

ICDAR 2025 Competition on End-to-End Document Image Machine Translation Towards Complex Layouts

Document Image Machine Translation (DIMT) seeks to translate text embedded in document images from o...

Open-World Motion Forecasting

Motion forecasting aims to predict the future trajectories of dynamic agents in the scene, enabling ...

FetalAgents: A Multi-Agent System for Fetal Ultrasound Image and Video Analysis

Fetal ultrasound (US) is the primary imaging modality for prenatal screening, yet its interpretation...

\$OneMillion-Bench: How Far are Language Agents from Human Experts?

As language models (LMs) evolve from chat assistants to long-horizon agents capable of multi-step re...

Perseus: Lineage-Aware Refinement of Kraken2 Taxonomic Classification for Long Read Metagenomes

Motivation: Long-read metagenomic sequencing improves assembly contiguity and enables genome-resolve...

How Long Can Unified Multimodal Models Generate Images Reliably? Taming Long-Horizon Interleaved Image Generation via Context Curation

Unified multimodal models hold the promise of generating extensive, interleaved narratives, weaving ...

CORE-Seg: Reasoning-Driven Segmentation for Complex Lesions via Reinforcement Learning

Medical image segmentation is undergoing a paradigm shift from conventional visual pattern matching ...

AI End-to-End Radiation Treatment Planning Under One Second

Artificial intelligence-based radiation therapy (RT) planning has the potential to reduce planning t...

K-MaT: Knowledge-Anchored Manifold Transport for Cross-Modal Prompt Learning in Medical Imaging

Large-scale biomedical vision-language models (VLMs) adapted on high-end imaging (e.g., CT) often fa...

Artificial Intelligence for Detecting Fetal Orofacial Clefts and Advancing Medical Education

Orofacial clefts are among the most common congenital craniofacial abnormalities, yet accurate prena...

An Integrated Molecular Atlas of Alzheimer's Disease

Alzheimer's disease (AD) is a complex neurodegenerative disorder with multifactorial etiology and wi...

Yolo-Key-6D: Single Stage Monocular 6D Pose Estimation with Keypoint Enhancements

Estimating the 6D pose of objects from a single RGB image is a critical task for robotics and extend...

Rethinking the Efficiency and Effectiveness of Reinforcement Learning for Radiology Report Generation

Radiologists highly desire fully automated AI for radiology report generation (R2G), yet existing ap...

Aging Out of the Blue: Estimating and Calibrating Region-specific Epigenetic Clocks for a Blue Zone via SuperLearner

Epigenetic clocks estimate biological age from DNA methylation patterns at CpG sites, providing robu...

GEN-KnowRD: Reframing AI for Rare Disease Recognition

Rare diseases affect over 300 million people worldwide, yet patients often endure years-long diagnos...

Multi-Omics Integration of Transcriptomics and Metabolomics with Machine Learning Uncovers Novel Risk Factors for Alzheimer's disease

Background: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive decl...

Retrieving Patient-Specific Radiomic Feature Sets for Transparent Knee MRI Assessment

Classical radiomic features are designed to quantify image appearance and intensity patterns. Compar...

MIRAGE: Knowledge Graph-Guided Cross-Cohort MRI Synthesis for Alzheimer's Disease Prediction

Reliable Alzheimer's disease (AD) diagnosis increasingly relies on multimodal assessments combining ...

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