Latest AI and machine learning research in geriatrics for healthcare professionals.
Single-point supervised infrared small target detection (IRSTD) drastically reduces dense annotation costs. Current state-of-the-art (SOTA) methods achieve high precision by recovering mask supervision through explicit, offline pseudo-label construction, such as multi-stage active learning and physics-driven mask generation. In this paper, we study a minimalist alternative: generating point-to-mas...
Introduction: Polypharmacy in older adults is associated with increased risks of adverse drug events and functional decline. Discharge summaries often contain deprescribing recommendations, but these are frequently overlooked due to documentation complexity. Objective: To develop and validate a two-stage hybrid system combining rule-based natural language processing (NLP) and large language model ...
Accurate prediction of conversion from Mild Cognitive Impairment (MCI) to Alzheimers Diseases (AD) is essential for early intervention, however, devel...
The prefrontal cortex (PFC), a brain region critical for executive and cognitive functions, is characterized by its protracted maturation extending th...
Structured information extraction from long, multilingual scanned financial documents is a core requirement in industrial KYC and compliance workflows...
The bottleneck in learning-based industrial defect detection is often limited not by model capacity, but by the scarcity of labeled defect data: defec...
Deploying tiny object perception on edge platforms is challenging because practical systems must satisfy both strict compute budgets and end-to-end la...
Federated fine-tuning provides a practical route to adapt large language models (LLMs) on edge devices without centralizing private data, yet in mobil...
Background & Aims: Accurate assessment of clinical malnutrition using anthropometric and functional indicators could improve the care of elderly traum...
Patients with dementia typically exhibit cognitive impairment, which is routinely assessed using the Mini-Mental State Examination (MMSE). Concurrentl...
Unified multimodal models typically rely on pretrained vision encoders and use separate visual representations for understanding and generation, creat...
Background Outcome after stroke varies according to stroke subtype by location, but healthcare systems data studies do not include subtyping informati...
Recent advances in vision-language models have demonstrated remarkable performance across diverse multi-modal tasks, including document question answe...
Recent text-to-image (T2I) models have demonstrated impressive capabilities in photorealistic synthesis and instruction following. However, their reli...
Internet photo collections exhibit an extremely long-tailed distribution: a few famous landmarks are densely photographed and easily reconstructed in ...
Chronological age is a potent determinant of clinical events, but it is conventionally treated as a linear function of time rather than a dynamic proc...
Patient-trial matching requires reasoning over long, heterogeneous electronic health records (EHRs) and complex eligibility criteria, posing significa...
We are pleased to submit our Original article entitled "Assessing medication-related burden and medication adherence among older patients from Central...
A significant fraction of the microbial diversity remains unclassified, hindering our understanding of microbial roles in health and ecosystems. State...
The insular cortex (IC) integrates diverse sensory and interoceptive signals to support emotional and cognitive functions, exhibiting topologically fu...