Neural networks : the official journal of the International Neural Network Society
Feb 22, 2020
In this paper, a three-dimensional fractional-order (FO) discrete Hopfield neural network (FODHNN) in the left Caputo discrete delta's sense is proposed, the dynamic behavior and synchronization of FODHNN are studied, and the system is applied to ima...
Artificial neural network (ANN) models can be trained to simulate the dynamic behavior of biological systems. In the present study, an ANN model was developed upon multilayer perceptron neural network architecture with 23-20-1 configuration to predic...
The aim of this paper was the detection of pathologies through respiratory sounds. The ICBHI (International Conference on Biomedical and Health Informatics) Benchmark was used. This dataset is composed of 920 sounds of which 810 are of chronic diseas...
Multi-organ segmentation is a challenging task due to the label imbalance and structural differences between different organs. In this work, we propose an efficient cascaded V-Net model to improve the performance of multi-organ segmentation by establ...
Journal of pain and symptom management
Feb 21, 2020
CONTEXT: Prior work using symptom burden to predict emergency department (ED) visits among patients with cancer has used traditional statistical methods such as logistic regression (LR). Machine learning approaches for prediction, such as artificial ...
PURPOSE: To develop and evaluate a novel method for pseudo-CT generation from multi-parametric MR images using multi-channel multi-path generative adversarial network (MCMP-GAN).
Journal of the American Chemical Society
Feb 21, 2020
This report describes the first application of the novel NMR-based machine learning tool "Small Molecule Accurate Recognition Technology" (SMART 2.0) for mixture analysis and subsequent accelerated discovery and characterization of new natural produc...
High-density surface electromyography (HD-sEMG) and deep learning technology are becoming increasingly used in gesture recognition. Based on electrode grid data, information can be extracted in the form of images that are generated with instant value...
PURPOSE: To accelerate coronary MRI acquisitions with arbitrary undersampling patterns by using a novel reconstruction algorithm that applies coil self-consistency using subject-specific neural networks.
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