OBJECTIVE: The objective of this article was to compare the performances of health care-associated infection (HAI) detection between deep learning and conventional machine learning (ML) methods in French medical reports.
Sensory neuroscience aims to build models that predict neural responses and perceptual behaviors, and that provide insight into the principles that give rise to them. For decades, artificial neural networks trained to perform perceptual tasks have at...
Epicardial adipose tissue is a visceral fat that has remained an entity of concern for decades owing to its high correlation with coronary heart disease. It continues to stump medical practitioners on the pretext of its relevance with pericardial fat...
For sparse sampling that accelerates magnetic resonance (MR) image acquisition, non-linear reconstruction algorithms have been developed, which incorporated patient specific a prior information. More generic a prior information could be acquired via ...
IEEE transactions on neural networks and learning systems
Mar 14, 2019
This paper from new perspectives discusses the global synchronization of multiple recurrent neural networks (MNNs) with time delays via impulsive coupling. A new concept (coupling strength) is introduced, it is a variable parameter and plays a key ro...
Computer methods and programs in biomedicine
Mar 14, 2019
BACKGROUND AND OBJECTIVE: Segmenting different tissue components in histopathological images is of great importance for analyzing tissues and tumor environments. In recent years, an encoder-decoder family of convolutional neural networks has increasi...
Deep learning is a significant step forward for developing autonomous tasks. One of its branches, computer vision, allows image recognition with high accuracy thanks to the use of convolutional neural networks (CNNs). Our goal was to train a CNN with...
Urban areas feature complex and heterogeneous land covers which create challenging issues for tree species classification. The increased availability of high spatial resolution multispectral satellite imagery and LiDAR datasets combined with the rece...
Machine-learning methods can assist with the medical decision-making processes at the both the clinical and diagnostic levels. In this article, we first review historical milestones and specific applications of computer-based medical decision support...
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