Neural networks : the official journal of the International Neural Network Society
Nov 26, 2024
Incomplete multi-view clustering addresses scenarios where data completeness cannot be guaranteed, diverging from traditional methods that assume fully observed features. Existing approaches often overlook high-order correlations present in multiple ...
OBJECTIVE: To enhance the efficiency, quality, and innovation capability of clinical trials, this paper introduces a novel model called CTEC-AC (Clinical Trial Eligibility Criteria Automatic Classification), aimed at structuring clinical trial eligib...
Neural networks : the official journal of the International Neural Network Society
Nov 23, 2024
Fraud detection for imbalanced datasets is challenging due to machine learning models inclination to learn the majority class. Imbalance in fraud detection datasets affects how graphs are built, an important step in many Graph Neural Networks (GNNs)....
Neural networks : the official journal of the International Neural Network Society
Nov 22, 2024
Deep graph clustering is a fundamental yet challenging task for graph data analysis. Recent efforts have witnessed significant success in combining autoencoder and graph convolutional network to explore graph-structured data. However, we observe that...
Neural networks : the official journal of the International Neural Network Society
Nov 20, 2024
Open-Set Domain Adaptation (OSDA) is designed to facilitate the transfer of knowledge from a source domain to a target domain, where the class space of the source is a subset of the target. The primary challenge in OSDA is the identification of share...
Recent developments in spatial transcriptomics (ST) technology have markedly enhanced the proposed capacity to comprehensively characterize gene expression patterns within tissue microenvironments while crucially preserving spatial context. However, ...
The accurate detection and quantification of rodent behavior forms a cornerstone of basic biomedical research. Current data-driven approaches, which segment free exploratory behavior into clusters, suffer from low statistical power due to multiple te...
Knowledge of B cell epitopes is critical to vaccine design, diagnostics, and therapeutics. As experimental validation for epitopes is time-consuming and costly, many in silico tools have been developed to computationally predict the B cell epitopes. ...
Neural networks : the official journal of the International Neural Network Society
Nov 5, 2024
The goal of debiasing in classification tasks is to train models to be less sensitive to correlations between a sample's target attribution and periodically occurring contextual attributes to achieve accurate classification. A prevalent method involv...