IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Apr 2, 2019
Deep learning has been successfully used in numerous applications because of its outstanding performance and the ability to avoid manual feature engineering. One such application is electroencephalogram (EEG)-based brain-computer interface (BCI), whe...
International journal of molecular sciences
Apr 2, 2019
Gene fusions have a very important role in the study of cancer development. In this regard, predicting the probability of protein fusion transcripts of developing into a cancer is a very challenging and yet not fully explored research problem. To thi...
IEEE journal of biomedical and health informatics
Apr 1, 2019
Control of blood glucose is essential for diabetes management. Current digital therapeutic approaches for subjects with type 1 diabetes mellitus such as the artificial pancreas and insulin bolus calculators leverage machine learning techniques for pr...
IEEE journal of biomedical and health informatics
Apr 1, 2019
Automatic polyp detection has been shown to be difficult due to various polyp-like structures in the colon and high interclass variations in polyp size, color, shape, and texture. An efficient method should not only have a high correct detection rate...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 1, 2019
The engineering of stable proteins is crucial for various industrial purposes. Several machine learning methods have been developed to predict changes in the stability of proteins corresponding to single point mutations. To improve the prediction acc...
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Apr 1, 2019
OBJECTIVES: The purpose of this study was to develop an automatic tracking method for the muscle cross-sectional area (CSA) on ultrasound (US) images using a convolutional neural network (CNN). The performance of the proposed method was evaluated and...
OBJECTIVE: To identify the feasibility of using a deep convolutional neural network (DCNN) for the detection and localization of hip fractures on plain frontal pelvic radiographs (PXRs). Hip fracture is a leading worldwide health problem for the elde...
Neural networks : the official journal of the International Neural Network Society
Apr 1, 2019
Brain image segmentation is of great importance not only for clinical use but also for neuroscience research. Recent developments in deep neural networks (DNNs) have led to the application of DNNs to brain image segmentation, which required extensive...
Neural networks : the official journal of the International Neural Network Society
Apr 1, 2019
The supervised learning methods for spiking neurons based on temporal encoding are important foundation for the development of spiking neural networks. During the learning process, the synaptic weights of a spiking neuron are adjusted to make the neu...
Clinical named entity recognition (CNER) is a fundamental and crucial task for clinical and translation research. In recent years, deep learning methods have achieved significant success in CNER tasks. However, these methods depend greatly on recurre...
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