Conventional COVID-19 testing methods have some flaws: they are expensive and time-consuming. Chest X-ray (CXR) diagnostic approaches can alleviate these flaws to some extent. However, there is no accurate and practical automatic diagnostic framework...
The value of coarsely labeled datasets in learning transferable representations for medical images is investigated in this work. Compared to fine labels which require meticulous effort to annotate, coarse labels can be acquired at a significantly low...
IEEE transactions on neural networks and learning systems
Feb 29, 2024
This article mainly proposes an evolutionary algorithm and its first application to develop therapeutic strategies for ecological evolutionary dynamics systems (EEDS), obtaining the balance between tumor cells and immune cells by rationally arranging...
IEEE transactions on neural networks and learning systems
Feb 29, 2024
For a better intention inference, we often try to figure out the emotional states of other people in social communications. Many studies on affective computing have been carried out to infer emotions through perceiving human states, i.e., facial expr...
BACKGROUND: Predicting outcome of breast cancer is important for selecting appropriate treatments and prolonging the survival periods of patients. Recently, different deep learning-based methods have been carefully designed for cancer outcome predict...
Using logistic regression and neural networks, the aim of this study was to compare model performance when predicting player draft outcome during the 2021 AFL National Draft. Physical testing, in-game movement and technical involvements were collecte...
Medical & biological engineering & computing
Feb 28, 2024
Micro-expressions (MEs) play such an important role in predicting a person's genuine emotions, as to make micro-expression recognition such an important resea rch focus in recent years. Most recent researchers have made efforts to recognize MEs with ...
Neural networks : the official journal of the International Neural Network Society
Feb 28, 2024
Spatial prediction tasks are challenging when observed samples are sparse and prediction samples are abundant. Gaussian processes (GPs) are commonly used in spatial prediction tasks and have the advantage of measuring the uncertainty of the interpola...
Neural networks : the official journal of the International Neural Network Society
Feb 28, 2024
Graph Neural Networks (GNNs) are a large class of relational models for graph processing. Recent theoretical studies on the expressive power of GNNs have focused on two issues. On the one hand, it has been proven that GNNs are as powerful as the Weis...
Variations in muscular contraction are known to significantly impact the quality of the generated EMG signal and the output decision of a proposed classifier. This is an issue when the classifier is further implemented in prosthetic hand design. Ther...
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