Journal of chemical information and modeling
Mar 3, 2020
We present a simple, modular graph-based convolutional neural network that takes structural information from protein-ligand complexes as input to generate models for activity and binding mode prediction. Complex structures are generated by a standard...
The development of deep learning algorithms for complex tasks in digital medicine has relied on the availability of large labeled training datasets, usually containing hundreds of thousands of examples. The purpose of this study was to develop a 3D d...
As one of the most popular approaches in artificial intelligence, deep learning (DL) has attracted a lot of attention in the medical physics field over the past few years. The goals of this topical review article are twofold. First, we will provide a...
IEEE transactions on bio-medical engineering
Mar 2, 2020
OBJECTIVE: To investigate the clinical utility of deep convolutional neural network (DCNN) tract classification as a new imaging tool in the preoperative evaluation of children with focal epilepsy (FE).
BACKGROUND: Experimental investigation of sleep-wake dynamics in animals is an important part of pharmaceutical development. Typically, it involves recording of electroencephalogram, electromyogram, locomotor activity, and electrooculogram. Visual id...
Medical & biological engineering & computing
Mar 2, 2020
Histopathological whole slide images of haematoxylin and eosin (H&E)-stained biopsies contain valuable information with relation to cancer disease and its clinical outcomes. Still, there are no highly accurate automated methods to correlate histolopa...
Medical & biological engineering & computing
Mar 2, 2020
A series of short events, called A-phases, can be observed in the human electroencephalogram (EEG) during Non-Rapid Eye Movement (NREM) sleep. These events can be classified in three groups (A1, A2, and A3) according to their spectral contents, and a...
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