BACKGROUND: Automatic segmentation and localization of lesions in mammogram (MG) images are challenging even with employing advanced methods such as deep learning (DL) methods. We developed a new model based on the architecture of the semantic segmen...
The promise of biotechnology is tempered by its potential for accidental or deliberate misuse. Reliably identifying telltale signatures characteristic to different genetic designers, termed 'genetic engineering attribution', would deter misuse, yet i...
IEEE/ACM transactions on computational biology and bioinformatics
Dec 8, 2020
We present an analysis of the problem of identifying biological context and associating it with biochemical events described in biomedical texts. This constitutes a non-trivial, inter-sentential relation extraction task. We focus on biological contex...
Motor imagery (MI) is an important part of brain-computer interface (BCI) research, which could decode the subject's intention and help remodel the neural system of stroke patients. Therefore, accurate decoding of electroencephalography- (EEG-) based...
The weight-updating methods have played an important role in improving the performance of neural networks. To ameliorate the oscillating phenomenon in training radial basis function (RBF) neural network, a fractional order gradient descent with momen...
Neural networks : the official journal of the International Neural Network Society
Dec 5, 2020
Knowledge graph reasoning aims to find reasoning paths for relations over incomplete knowledge graphs (KG). Prior works may not take into account that the rewards for each position (vertex in the graph) may be different. We propose the distance-aware...
Physical and engineering sciences in medicine
Dec 4, 2020
The highly contagious nature of Coronavirus disease 2019 (Covid-19) resulted in a global pandemic. Due to the relatively slow and taxing nature of conventional testing for Covid-19, a faster method needs to be in place. The current researches have su...
IEEE journal of biomedical and health informatics
Dec 4, 2020
Automated retinal vessel segmentation is among the most significant application and research topics in ophthalmologic image analysis. Deep learning based retinal vessel segmentation models have attracted much attention in the recent years. However, c...
IEEE journal of biomedical and health informatics
Dec 4, 2020
The direct analysis of 3D Optical Coherence Tomography (OCT) volumes enables deep learning models (DL) to learn spatial structural information and discover new bio-markers that are relevant to glaucoma. Downsampling 3D input volumes is the state-of-a...
Stacking-based deep neural network (S-DNN) is aggregated with pluralities of basic learning modules, one after another, to synthesize a deep neural network (DNN) alternative for pattern classification. Contrary to the DNNs trained from end to end by ...
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