For tumor tracking therapy, precise knowledge of tumor position in real-time is very important. A technique using single x-ray projection based on a convolutional neural network (CNN) was recently developed which can achieve accurate tumor localizati...
For spatiotemporal learning with neural networks, hyperparameters are often set manually by a human expert. This is especially the case with multiple timescale networks that require a careful setting of the values of timescales in order to learn spat...
is widely used in traditional Chinese medicine (TCM). Ganoderic acid A and D are the main bioactive components with anticancer effects in . To obtain the maximum content of two compounds from , a novel extraction method, an ionic liquid-based ultras...
Similarity-based search of sequence collections is a core task in bioinformatics, one dominated for most of the genomic era by exact and heuristic alignment-based algorithms. However, even efficient heuristics such as BLAST may not scale to the data ...
The utilization of entomological specimens such as larvae (maggots) for the estimation of time since oviposition (i.e., egg laying) for post mortem interval determination, or for estimation of time since tissue infestation (in investigations of elder...
OBJECTIVE: To assess the utility of machine learning algorithms for automatically estimating prognosis in patients with repaired tetralogy of Fallot (ToF) using cardiac magnetic resonance (CMR).
The heterogeneity of traumatic brain injury (TBI) remains a core challenge for the success of interventional clinical trials. Data-driven approaches for patient stratification may help to identify TBI patient phenotypes during the acute injury period...
Intensive-care clinicians are presented with large quantities of measurements from multiple monitoring systems. The limited ability of humans to process complex information hinders early recognition of patient deterioration, and high numbers of monit...
Neural networks : the official journal of the International Neural Network Society
Mar 7, 2020
The global exponential stabilization and lag synchronization control of delayed inertial neural networks (INNs) are investigated. By constructing nonnegative function and employing inequality techniques, several new results about exponential stabiliz...
Neural networks : the official journal of the International Neural Network Society
Mar 7, 2020
The significant contribution of this paper is the addressing the stability issue of neutral-type Cohen-Grossberg neural networks possessing multiple time delays in the states of the neurons and multiple neutral delays in time derivative of states of ...