Drug-drug interactions account for up to 30% of adverse drug reactions. Increasing prevalence of electronic health records (EHRs) offers a unique opportunity to build machine learning algorithms to identify drug-drug interactions that drive adverse e...
IEEE transactions on neural networks and learning systems
Jul 6, 2021
Due to the high availability of large-scale annotated image datasets, knowledge transfer from pretrained models showed outstanding performance in medical image classification. However, building a robust image classification model for datasets with da...
IEEE transactions on neural networks and learning systems
Jul 6, 2021
We consider a human-in-the-loop scenario in the context of low-shot learning. Our approach was inspired by the fact that the viability of samples in novel categories cannot be sufficiently reflected by those limited observations. Some heterogeneous s...
IEEE transactions on neural networks and learning systems
Jul 6, 2021
The ability to learn more concepts from incrementally arriving data over time is essential for the development of a lifelong learning system. However, deep neural networks often suffer from forgetting previously learned concepts when continually lear...
IEEE transactions on neural networks and learning systems
Jul 6, 2021
This brief presents an intrinsic plasticity (IP)-driven neural-network-based tracking control approach for a class of nonlinear uncertain systems. Inspired by the neural plasticity mechanism of individual neuron in nervous systems, a learning rule re...
IEEE transactions on neural networks and learning systems
Jul 6, 2021
Neural networks (NNs) are effective machine learning models that require significant hardware and energy consumption in their computing process. To implement NNs, stochastic computing (SC) has been proposed to achieve a tradeoff between hardware effi...
IEEE transactions on neural networks and learning systems
Jul 6, 2021
Emotions composed of cognizant logical reactions toward various situations. Such mental responses stem from physiological, cognitive, and behavioral changes. Electroencephalogram (EEG) signals provide a noninvasive and nonradioactive solution for emo...
Computational intelligence and neuroscience
Jul 6, 2021
Deep learning is the latest trend of machine learning and artificial intelligence research. As a new field with rapid development over the past decade, it has attracted more and more researchers' attention. Convolutional Neural Network (CNN) model is...
Data classification is one of the most commonly used applications of machine learning. The are many developed algorithms that can work in various environments and for different data distributions that perform this task with excellence. Classification...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jul 5, 2021
This research aims at studying the ability of using diffuse reflectance spectroscopy (DRS) for discriminating or classifying coal samples into different ranks. Spectral characteristics such as the shape of the spectral profile, slope, absorption inte...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.