Latest AI and machine learning research in geriatrics for healthcare professionals.
Background: Identifying early brain-based markers of cognitive decline is critical for preventive strategies in Alzheimer's disease. Individuals with a familial risk may exhibit subtle functional brain changes years before clinical symptoms emerge. This exploratory study examined whether baseline functional brain network topology differentiates high-risk cognitively normal older adults who later p...
Despite recent successes, test-time scaling - i.e., dynamically expanding the token budget during inference as needed - remains brittle for vision-language models (VLMs): unstructured chains-of-thought about images entangle perception and reasoning, leading to long, disorganized contexts where small perceptual mistakes may cascade into completely wrong answers. Moreover, expensive reinforcement le...
Accurate prediction of outcomes is crucial for clinical decision-making and personalized patient care. Supervised machine learning algorithms, which a...
High-quality annotated datasets are crucial for advancing machine learning in medical image analysis. However, a critical gap exists: most datasets ei...
Aging and genetic risk shape the molecular programs that confer cellular vulnerability in Alzheimer's disease (AD), but whether these programs differ ...
Decision-making in drug development spans heterogeneous stages from molecular design to clinical optimization, yet computer-aided workflows across sta...
Opportunities for medical students to gain practical experience in vaginal births are increasingly constrained by shortened clinical rotations, patien...
Timely and accurate diagnosis of dementia remains a critical yet challenging task. Although machine learning (ML) techniques have shown considerable p...
Background: Amyotrophic lateral sclerosis (ALS) is clinically heterogeneous, and genetic modifiers may drive molecular endophenotypes without obvious ...
Early detection of dementia enables timely intervention and better care planning. Electroencephalography, being accessible and noninvasive, offers a p...
Genetic-based risk prediction is becoming increasingly available for a wide range of common diseases thanks to the growth of large-scale biobanks and ...
Optical coherence tomography (OCT) has revolutionized retinal disease diagnosis with its high-resolution and three-dimensional imaging nature, yet its...
Inverse scattering in optical coherence tomography (OCT) seeks to recover both structural images and intrinsic tissue optical properties, including re...
DNA methylation is a central epigenetic modification that regulates gene expression, maintains genomic stability, and guides cellular differentiation....
Early and accurate diagnosis of Alzheimer's disease (AD) remains a critical challenge in neuroimaging-based clinical decision support systems. In this...
Limited access to medical infrastructure forces elderly and vulnerable patients to rely on home-based care, often leading to neglect and poor adherenc...
Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by widespread dysregulation of gene expression and regulatory pathways....
The development of large vision language models drives the demand for managing, and applying massive amounts of multimodal data, making OCR technology...
High-dimensional structural MRI (sMRI) images are widely used for Alzheimer's Disease (AD) diagnosis. Most existing methods for sMRI representation le...
Charts are a fundamental visualization format for structured data analysis. Enabling end-to-end chart editing according to user intent is of great pra...