Artificial intelligence has made significant strides in predicting major adverse cardiovascular events (MACE) in patients with acute myocardial infarction (AMI) following percutaneous coronary intervention. However, most existing methods rely solely ... read more
The rapid expansion of AI, large-scale simulation, and data-intensive research has increased demand for GPU resources in national supercomputing systems. However, allocation mechanisms in many centers remain primarily workload-driven, which may not f... read more
Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related death worldwide, yet current prognostic stratification is hindered by tumor heterogeneity. Here, we developed a deep learning radiomics model (... read more
To evaluate the feasibility and application value of a transfer learning-based artificial intelligence (AI) system for wound recognition and suture position planning in patients with corneal lacerations. In this prospective, non-randomized controlled... read more
Fluctuations in blood glucose during acute neurocritical illness are associated with poor outcomes, but the role of stress hyperglycemia ratio (SHR) in predicting outcomes across diverse neurocritical conditions remains unclear. This study evaluated ... read more
BACKGROUND: Ultra-processed foods (UPF) dominate modern food systems and contribute significantly to early-life diets. However, the multilevel predictors of UPF consumption in early childhood, from family factors to neighbourhood environments, remain... read more
Journal of imaging informatics in medicine
Mar 6, 2026
The National Institutes of Health Stroke Scale (NIHSS) is a quantitative tool, grading neurological deficits and guiding acute stroke management; however, bedside scoring is labor-intensive, time-consuming, and subject to interrater variability. This... read more
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