IEEE/ACM transactions on computational biology and bioinformatics
Jun 3, 2021
Deep learning is widely used in the medical field owing to its high accuracy in medical image classification and biological applications. However, under collaborative deep learning, there is a serious risk of information leakage based on the deep con...
IEEE/ACM transactions on computational biology and bioinformatics
Jun 3, 2021
Assessing the location and extent of lesions caused by chronic stroke is critical for medical diagnosis, surgical planning, and prognosis. In recent years, with the rapid development of 2D and 3D convolutional neural networks (CNN), the encoder-decod...
IEEE/ACM transactions on computational biology and bioinformatics
Jun 3, 2021
The tracking of densely packed plant cells across microscopy image sequences is very challenging, because their appearance change greatly over time. A local graph matching algorithm was proposed to track such cells by exploiting the tight spatial top...
IEEE/ACM transactions on computational biology and bioinformatics
Jun 3, 2021
High-risk prediction of cardiovascular disease is of great significance and impendency in medical fields with the increasing phenomenon of sub-health these years. Most existing pathological methods for the prognosis prediction are either costly or pr...
Neural networks : the official journal of the International Neural Network Society
Jun 2, 2021
Inspired by the success of classical neural networks, there has been tremendous effort to develop classical effective neural networks into quantum concept. In this paper, a novel hybrid quantum-classical neural network with deep residual learning (Re...
Neural networks : the official journal of the International Neural Network Society
Jun 2, 2021
Graph convolutional networks (GCNs) have been widely used for representation learning on graph data, which can capture structural patterns on a graph via specifically designed convolution and readout operations. In many graph classification applicati...
Environmental science and pollution research international
Jun 2, 2021
Bronchopneumonia is the most common infectious disease in children, and it seriously endangers children's health. In this paper, a deep neural network combining long short-term memory (LSTM) layers and fully connected layers was proposed to predict t...
Computer methods and programs in biomedicine
Jun 2, 2021
BACKGROUND: Diagnosing brain tumours remains a challenging task in clinical practice. Despite their questionable accuracy, magnetic resonance image (MRI) scans are presently considered the optimal facility for assessing the growth of tumours. However...
Neural networks : the official journal of the International Neural Network Society
Jun 2, 2021
Datasets with missing values are very common in real world applications. GAIN, a recently proposed deep generative model for missing data imputation, has been proved to outperform many state-of-the-art methods. But GAIN only uses a reconstruction los...
International journal of molecular sciences
Jun 2, 2021
The new advances in deep learning methods have influenced many aspects of scientific research, including the study of the protein system. The prediction of proteins' 3D structural components is now heavily dependent on machine learning techniques tha...