After Deep Learning (DL) regained popularity recently, the Artificial Intelligence (AI) or Machine Learning (ML) field is undergoing rapid growth concerning research and real-world application development. Deep Learning has generated complexities in ...
BMC medical informatics and decision making
Apr 3, 2021
BACKGROUND: Artificial intelligence (AI) research is highly dependent on the nature of the data available. With the steady increase of AI applications in the medical field, the demand for quality medical data is increasing significantly. We here desc...
Medical oncology (Northwood, London, England)
Apr 3, 2021
Gliomas are one of the most devastating primary brain tumors which impose significant management challenges to the clinicians. The aggressive behaviour of gliomas is mainly attributed to their rapid proliferation, unravelled genomics and the blood-br...
Annali di igiene : medicina preventiva e di comunita
Apr 2, 2021
Nowadays, digital information has increased exponentially in every field to such an extent that it generates huge amounts of electronic data, namely Big Data. In the field of Artificial Intelligence, Machine Learning can be exploited in order to tran...
Annual review of biomedical engineering
Apr 2, 2021
The widespread availability of high-performance computing and the popularity of artificial intelligence (AI) with machine learning and deep learning (ML/DL) algorithms at the helm have stimulated the development of many applications involving the use...
OBJECTIVE: H3K27M mutation in gliomas has prognostic implications. Previous magnetic resonance imaging (MRI) studies have reported variable rates of tumoral enhancement, necrotic changes, and peritumoral edema in H3K27M-mutant gliomas, with no distin...
IEEE transactions on neural networks and learning systems
Apr 2, 2021
Electronic medical records (EMRs) play an important role in medical data mining and sequential data learning. In this article, we propose to use a sequential neural network with dynamic content-based memories to predict future medications, given EMRs...
IEEE transactions on neural networks and learning systems
Apr 2, 2021
The Bayesian method is capable of capturing real-world uncertainties/incompleteness and properly addressing the overfitting issue faced by deep neural networks. In recent years, Bayesian neural networks (BNNs) have drawn tremendous attention to artif...
IEEE transactions on neural networks and learning systems
Apr 2, 2021
In this article, by introducing a signed graph to describe the coopetition interactions among network nodes, the mathematical model of multiple memristor-based neural networks (MMNNs) with antagonistic interactions is established. Since the cooperati...
IEEE transactions on neural networks and learning systems
Apr 2, 2021
This article is concerned with the tracking control problem for uncertain high-order nonlinear systems in the presence of input saturation. A finite-time control strategy combined with neural state observer and command filtered backstepping is propos...
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