BACKGROUND: The mitotic count in breast carcinoma is an important prognostic marker. Unfortunately substantial inter- and intra-laboratory variation exists when pathologists manually count mitotic figures. Artificial intelligence (AI) coupled with wh...
Journal of biomolecular structure & dynamics
Jul 3, 2020
Deep learning models are widely used in the automatic analysis of radiological images. These techniques can train the weights of networks on large datasets as well as fine tuning the weights of pre-trained networks on small datasets. Due to the small...
Psychotherapy research : journal of the Society for Psychotherapy Research
Jul 3, 2020
Understanding patient responses to psychotherapy is important in developing effective interventions. However, coding patient language is a resource-intensive exercise and difficult to perform at scale. Our aim was to develop a deep learning model to...
OBJECTIVES: The purpose of this study was to automatically diagnose odontogenic cysts and tumors of both jaws on panoramic radiographs using deep learning. We proposed a novel framework of deep convolution neural network (CNN) with data augmentation ...
Neural networks : the official journal of the International Neural Network Society
Jul 3, 2020
Learning with incomplete labels in Neural Networks has been actively investigated these last years. Among different kinds of incomplete labels, we investigate incomplete pixel-level labels which are tackled in many concrete problems. One of the chall...
Neural networks : the official journal of the International Neural Network Society
Jul 3, 2020
The accuracy of deep learning, i.e., deep neural networks, can be characterized by dividing the total error into three main types: approximation error, optimization error, and generalization error. Whereas there are some satisfactory answers to the p...
Computer methods and programs in biomedicine
Jul 3, 2020
BACKGROUND AND OBJECTIVES: Surface Electromyography (sEMG) is used mostly for neuromuscular diagnosis, assistive technology, physical rehabilitation, and human-computer interactions. Achieving a precise and lightweight method along with low latency f...
Translational research of many disease areas requires a longitudinal understanding of disease development and progression across all biologically relevant scales. Several corresponding studies are now available. However, to compile a comprehensive pi...
Due to acromegaly's insidious onset and slow progression, its diagnosis is usually delayed, thus causing severe complications and treatment difficulty. A convenient screening method is imperative. Based on our previous work, we herein developed a new...
One drug's pharmacological activity may be changed unexpectedly, owing to the concurrent administration of another drug. It is likely to cause unexpected drug-drug interactions (DDIs). Several machine learning approaches have been proposed to predict...
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