Neural networks : the official journal of the International Neural Network Society
Mar 25, 2025
Recent advances in deep learning for semantic segmentation models have introduced dynamic segmentation methods as opposed to static segmentation methods represented by full convolutional networks. Dynamic prediction methods replace static classifiers...
BACKGROUND: The S100 family of calcium-binding proteins (S100s) had been tightly related to the biological processes of various cardiovascular diseases. This study aims to investigate the expression of S100s in Atherosclerosis (AS) and explore their ...
Neural networks : the official journal of the International Neural Network Society
Mar 25, 2025
When training and test graph samples follow different data distributions, graph out-of-distribution (OOD) detection becomes an indispensable component of constructing the reliable and safe graph learning systems. Motivated by the significant progress...
Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Mar 25, 2025
PURPOSE: Prostate cancer (PCa) is the most frequently diagnosed malignancy among men in Germany. Advances in diagnostics and treatment have transformed PCa into a chronic disease. Given the heterogeneity of PCa, there is a need for additional stratif...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 25, 2025
PURPOSE: Information on deep learning (DL) tumor segmentation accuracy on a voxel and a structure level is essential for clinical introduction. In a previous study, a DL model was developed for oropharyngeal cancer (OPC) primary tumor (PT) segmentati...
BACKGROUND: Accurate preoperative prediction of spread through air spaces (STAS) in primary lung adenocarcinoma (LUAD) is critical for optimizing surgical strategies and improving patient outcomes.
RATIONALE AND OBJECTIVE: Clinical workload can fluctuate daily in radiology practice. We sought to design, validate, and implement an efficient and sustainable machine learning model to forecast daily clinical image interpretation workload.
BACKGROUND: The application of artificial intelligence (AI) in the field of automatic imaging report labeling faces the challenge of manually labeling large datasets.
Extracellular vesicles (EVs) are lipid-enclosed particles released from cells, containing lipids, DNA, RNA, metabolites, and cytosolic and cell surface proteins. EVs support intercellular communication and orchestrate organogenesis by transferring bi...
PURPOSE: Variability in the interpretation of videourodynamics studies limits reliable classification of kidney injury risk for patients with spina bifida. We developed machine learning models to predict incident hydronephrosis in patients with spina...
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