International journal of medical informatics
Feb 23, 2025
Net benefit is the most widely used metric for evaluating the clinical utility of medical prediction models. The approach applies decision analytic theory to weight true and false positives depending on the relative consequences of different decision...
BACKGROUND: Identifying fractured endodontic instruments (FEIs) in periapical radiographs (PAs) is a critical yet challenging aspect of root canal treatment (RCT) due to anatomical complexities and overlapping structures. Deep learning (DL) models of...
Neural networks : the official journal of the International Neural Network Society
Feb 22, 2025
Few Labeled Node Classification (FLNC) is a challenging subtask of node classification, where training nodes are extremely limited, often with only one or two labels per class. While Graph Neural Networks (GNNs) show promise, they often suffer from f...
Protein sequence design is a highly challenging task, aimed at discovering new proteins that are more functional and producible under laboratory conditions than their natural counterparts. Deep learning-based approaches developed to address this prob...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 22, 2025
Accurate segmentation of hepatic vessels is pivotal for guiding preoperative planning in ablation surgery utilizing CT images. While non-contrast CT images often lack observable vessels, we focus on segmenting hepatic vessels within preoperative MR i...
Neural networks : the official journal of the International Neural Network Society
Feb 22, 2025
This paper presents a specified-time resilient formation maneuver control approach for second-order nonlinear multi-robot systems under false data injection (FDI) attacks, incorporating an offline neural network. Building on existing works in integra...
Neural networks : the official journal of the International Neural Network Society
Feb 22, 2025
Learning from limited data has been extensively studied in machine learning, considering that deep neural networks achieve optimal performance when trained using a large amount of samples. Although various strategies have been proposed for centralize...
Neural networks : the official journal of the International Neural Network Society
Feb 22, 2025
Graph Neural Network (GNN) is effective in graph mining and has become a dominant solution to the node classification task. Recently, a series of label reuse approaches emerged to boost the node classification performance of GNN. They repeatedly inpu...
Neural networks : the official journal of the International Neural Network Society
Feb 22, 2025
Next Point-of-Interest (POI) recommendation is crucial in location-based applications, analyzing user behavior patterns from historical trajectories. Existing studies usually use graph structures and attention mechanisms for sequential prediction wit...
Neural networks : the official journal of the International Neural Network Society
Feb 22, 2025
This paper proposes a strictly predefined-time convergent and anti-noise fractional-order zeroing neural network (SPTC-AN-FOZNN) model, meticulously designed for addressing time-variant quadratic programming (TVQP) problems. This model marks the firs...
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