IEEE transactions on neural networks and learning systems
Jan 4, 2021
Learning vector quantization (LVQ) is a simple and efficient classification method, enjoying great popularity. However, in many classification scenarios, such as electroencephalogram (EEG) classification, the input features are represented by symmetr...
IEEE transactions on neural networks and learning systems
Jan 4, 2021
The state-of-the-art multitask multiview (MTMV) learning tackles a scenario where multiple tasks are related to each other via multiple shared feature views. However, in many real-world scenarios where a sequence of the multiview task comes, the high...
IEEE transactions on neural networks and learning systems
Jan 4, 2021
Open-domain dialog generation, which is a crucial component of artificial intelligence, is an essential and challenging problem. In this article, we present a personalized dialog system, which leverages the advantages of multitask learning and reinfo...
IEEE transactions on neural networks and learning systems
Jan 4, 2021
Deep convolutional neural networks have been widely used in numerous applications, but their demanding storage and computational resource requirements prevent their applications on mobile devices. Knowledge distillation aims to optimize a portable st...
Neural networks : the official journal of the International Neural Network Society
Jan 2, 2021
A machine learning meshing scheme for the generation of 2-D simplicial meshes is proposed based on the predictions of neural networks. The data extracted from meshed contours are utilized to train neural networks which are used to approximate the num...
Interdisciplinary sciences, computational life sciences
Jan 2, 2021
Corona virus disease (COVID-19) acknowledged as a pandemic by the WHO and mankind all over the world is vulnerable to this virus. Alternative tools are needed that can help in diagnosis of the coronavirus. Researchers of this article investigated the...
Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
Jan 2, 2021
OBJECTIVE: Having shown promise in other medical fields, we sought to determine whether machine learning (ML) models perform better than usual care in diagnostic and prognostic prediction for emergency department (ED) patients.
In this paper, we introduce a network machine learning method to identify potential bioactive anti-COVID-19 molecules in foods based on their capacity to target the SARS-CoV-2-host gene-gene (protein-protein) interactome. Our analyses were performed ...
International journal of biological sciences
Jan 1, 2021
With the continuous development of medical image informatics technology, more and more high-throughput quantitative data could be extracted from digital medical images, which has resulted in a new kind of omics-Radiomics. In recent years, in addition...
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