The Journal of investigative dermatology
Mar 31, 2020
Although deep learning algorithms have demonstrated expert-level performance, previous efforts were mostly binary classifications of limited disorders. We trained an algorithm with 220,680 images of 174 disorders and validated it using Edinburgh (1,3...
In toxicity evaluation based on the nuclear receptor signalling pathway, in silico prediction tools are used for the detection of the early stages of long-term toxicities, the prioritization of newly synthesized chemicals and the acquisition of the s...
INTRODUCTION: Deep discriminative and generative neural-network models are becoming an integral part of the modern approach to ligand-based novel drug discovery. The variety of different architectures of neural networks, the methods of their training...
The practicability of deep learning techniques has been demonstrated by their successful implementation in varied fields, including diagnostic imaging for clinicians. In accordance with the increasing demands in the healthcare industry, techniques fo...
Deep convolutional neural network (DCNN) has shown great success in various medical image segmentation tasks, including organ-at-risk (OAR) segmentation from computed tomography (CT) images. However, most studies use the dataset from the same source(...
This review covers original articles using deep learning in the biophotonic field published in the last years. In these years deep learning, which is a subset of machine learning mostly based on artificial neural network geometries, was applied to a ...
Phonocardiogram (PCG) signals reflect the mechanical activity of the heart. Previous studies have reported that PCG signals contain heart murmurs caused by coronary artery disease (CAD). However, the murmurs caused by CAD are very weak and rarely hea...
Daily activity forecasts play an important role in the daily lives of residents in smart homes. Category forecasts and occurrence time forecasts of daily activity are two key tasks. Category forecasts of daily activity are correlated with occurrence ...
The human epigenome has been experimentally characterized by thousands of measurements for every basepair in the human genome. We propose a deep neural network tensor factorization method, Avocado, that compresses this epigenomic data into a dense, i...
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