To systematically evaluate and compare the performance of large language models (LLMs) in answering osteoporosis-related frequently asked questions (FAQs) derived from international osteoporosis-related associations. A standardized question bank was ... read more
Objective.Attention deficit hyperactivity disorder (ADHD) remains challenging to diagnose objectively and often relies on subjective clinical assessments. Although graph neural network-based methods have been widely used for ADHD identification, most... read more
Predicting who will deteriorate under stress is important for targeting mental-health support; yet, treatment-effect models are rarely tested across populations. We evaluate a domain-adaptive neural uplift model on three heterogeneous cohorts-medical... read more
This study comprehensively reviews human-machine collaborative decision-making (HMCD) methods and applications across management science, the military, healthcare, and manufacturing. We propose a dual-layer analytical framework. The first layer decom... read more
Children with beta-thalassemia major (β-TM) are at risk of neurodevelopmental or cognitive impairment. In this study, we developed SurfGNN, a surface-based graph neural network model, to estimate brain age from cortical morphological features extract... read more
Continuous cardiovascular monitoring via wearable devices is critical for early disease detection, yet existing pulse signal analysis methods struggle to achieve both high accuracy and real-time performance under noisy, imbalanced conditions. We prop... read more
Depression and psoriasis are highly comorbid, yet their shared molecular mechanisms remain poorly understood. Utilizing cross-sectional data from NHANES and Mendelian randomization (MR), a significant association and causal link between depression an... read more
Data contamination, from recording errors to extreme outliers, can compromise statistical models by biasing predictions, inflating prediction errors, and, in severe cases, destabilizing performance in high-dimensional settings. Although contamination... read more
Background: Large-scale estimates of animal-to-human drug translation and the study characteristics associated with successful translation remain limited. The expanding preclinical literature also challenges manual evidence synthesis. We developed a ... read more
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