BACKGROUND: Early sepsis diagnosis in children remains challenging due to nonspecific presentations. This study aimed to develop an interpretable machine learning (ML) model to improve early prediction. METHODS: We conducted a retrospective cohort st... read more
The integration of artificial intelligence (AI) into medical training is accelerating faster than the educational frameworks designed to govern it. This Perspective identifies a risk that has received insufficient attention: that trainees who rely on... 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
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
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