BMC medical informatics and decision making
Aug 20, 2020
BACKGROUND: As of today, cancer is still one of the most prevalent and high-mortality diseases, summing more than 9 million deaths in 2018. This has motivated researchers to study the application of machine learning-based solutions for cancer detecti...
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Aug 20, 2020
BACKGROUND: Tissue characterisation with cardiovascular magnetic resonance (CMR) parametric mapping has the potential to detect and quantify both focal and diffuse alterations in myocardial structure not assessable by late gadolinium enhancement. Nat...
Polycystic ovary syndrome (PCOS) is one of the most common metabolic and reproductive endocrinopathies. However, few studies have tried to develop a diagnostic model based on gene biomarkers. In this study, we applied a computational method by combin...
Neural networks : the official journal of the International Neural Network Society
Aug 19, 2020
Convolutional neural networks (CNNs) are widely used to recognize the user's state through electroencephalography (EEG) signals. In the previous studies, the EEG signals are usually fed into the CNNs in the form of high-dimensional raw data. However,...
Neural networks : the official journal of the International Neural Network Society
Aug 19, 2020
In recent years, convolutional neural networks have been successfully applied to single image super-resolution (SISR) tasks, making breakthrough progress both in accuracy and speed. In this work, an improved dual-scale residual network (IDSRN), achie...
Journal of chemical information and modeling
Aug 19, 2020
Deep learning has demonstrated significant potential in advancing state of the art in many problem domains, especially those benefiting from automated feature extraction. Yet, the methodology has seen limited adoption in the field of ligand-based vir...
To achieve the satisfactory performance of human action recognition, a central task is to address the sub-action sharing problem, especially in similar action classes. Nevertheless, most existing convolutional neural network (CNN)-based action recogn...
Fully convolutional neural network (FCN) has achieved great success in semantic segmentation. However, the performance of the FCN is generally compromised for multi-object segmentation. Multi-organ segmentation is very common while challenging in the...
Visually inferring material properties is crucial for many tasks, yet poses significant computational challenges for biological vision. Liquids and gels are particularly challenging due to their extreme variability and complex behaviour. We reasoned ...
Journal of the Royal Society, Interface
Aug 19, 2020
A major issue in translation of the artificial intelligence platforms for automatic segmentation of echocardiograms to clinics is their generalizability. The present study introduces and verifies a novel generalizable and efficient fully automatic mu...
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