International journal of computer assisted radiology and surgery
Apr 5, 2025
PURPOSE: Metal artifacts remain a persistent issue in intraoperative CBCT imaging. Particularly in orthopedic and trauma applications, these artifacts obstruct clinically relevant areas around the implant, reducing the modality's clinical value. Meta...
Journal of applied clinical medical physics
Apr 5, 2025
BACKGROUND: The use of deep learning-based auto-contouring algorithms in various treatment planning services is increasingly common. There is a notable deficit of commercially or publicly available models trained on large or diverse datasets containi...
Deep learning shows promise in automated brain tumour segmentation, but it depends on costly expert annotations. Recent advances in unsupervised learning offer an alternative by using synthetic data for training. However, the discrepancy between real...
Floating garbage removal is an essential environmental strategy to reduce water pollution and achieve environmental sustainability, and it is a pressing issue for global ecological restoration. Under the interference of complex environments, floating...
Ecotoxicology and environmental safety
Apr 5, 2025
Identification of groundwater pollution sources (IGPSs) is a prerequisite for pollution remediation and pollution risk prediction. Data assimilation approaches have been used extensively in IGPSs field in recent years. A data assimilation approach-un...
International journal of molecular sciences
Apr 5, 2025
This study explores the role of intrinsically disordered regions (IDRs) in the SARS-CoV-2 proteome and their potential as targets for small-molecule drug discovery. Experimentally validated intrinsic disordered regions from the literature were utiliz...
BACKGROUND: Chromosomes of species exhibit a variety of high-dimensional organizational features, and chromatin loops, which are fundamental structures in the three-dimensional (3D) structure of the genome. Chromatin loops are visible speckled patter...
Identifying DNA-binding proteins and their binding residues is critical for understanding diverse biological processes, but conventional experimental approaches are slow and costly. Existing machine learning methods, while faster, often lack accuracy...
OBJECTIVE: To develop a deep learning (DL) model for the detection of spinal cord (SC) multiple sclerosis (MS) lesions from both sagittal T2 and short tau inversion recovery (STIR) sequences and to investigate whether such a model could improve the p...
OBJECTIVE: To develop an automated method for the joint and consistent evaluation of emphysema and mortality risk that provides quantification of data and model uncertainty.
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