PURPOSE: While the recommended analysis method for magnetic resonance spectroscopy data is linear combination model (LCM) fitting, the supervised deep learning (DL) approach for quantification of MR spectroscopy (MRS) and MR spectroscopic imaging (MR...
Persistent contaminants from different industries have already caused significant risks to the environment and public health. In this study, a data set containing 1306 not readily biodegradable (NRB) and 622 readily biodegradable (RB) chemicals was c...
Journal of the Royal Society, Interface
Apr 5, 2023
The potential for complex systems to exhibit tipping points in which an equilibrium state undergoes a sudden and often irreversible shift is well established, but prediction of these events using standard forecast modelling techniques is quite diffic...
There is a vast development of artificial intelligence (AI) in recent years. Computational technology, digitized data collection and enormous advancement in this field have allowed AI applications to penetrate the core human area of specialization. I...
Spike sorting plays an essential role to obtain electrophysiological activity of single neuron in the fields of neural signal decoding. With the development of electrode array, large numbers of spikes are recorded simultaneously, which rises the need...
INTRODUCTION: This study aimed to evaluate the use of deep convolutional neural network (DCNN) algorithms to detect clinical features and predict the three-year outcome of endodontic treatment on preoperative periapical radiographs.
Medical imaging deep learning models are often large and complex, requiring specialized hardware to train and evaluate these models. To address such issues, we propose the PocketNet paradigm to reduce the size of deep learning models by throttling th...
IEEE journal of biomedical and health informatics
Apr 4, 2023
Interpretability often seeks domain-specific facts, which is understandable to human, from deep-learning (DL) or other machine-learning (ML) models of black-box nature. This is particularly important to establish transparency in ML model's inner-work...
IEEE journal of biomedical and health informatics
Apr 4, 2023
The lack of a gold standard synergy quantification method for chemotherapeutic drug combinations warrants the consideration of different synergy metrics to develop efficient predictive models. Furthermore, neglecting combination sensitivity may lead ...
IEEE transactions on neural networks and learning systems
Apr 4, 2023
A single dendritic neuron model (DNM) that owns the nonlinear information processing ability of dendrites has been widely used for classification and prediction. Complex-valued neural networks that consist of a number of multiple/deep-layer McCulloch...
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