This paper presents a comprehensive overview of modelling, simulation and implementation
of neural networks, taking into account that two aims have emerged in this area: the …

The Precision Neurology development process implements systems theory with system
biology and neurophysiology in a parallel, bidirectional research path: a combined …

As artificial intelligence is being increasingly used for high-stakes applications, it is
becoming more and more important that the models used be interpretable. Bayesian …

Networks represent relationships between entities in many complex systems, spanning from
online social interactions to biological cell development and brain connectivity. In many …

Alzheimer's disease (AD) is an irreversible neurodegenerative brain disorder that degrades
the memory and cognitive ability in elderly people. The main reason for memory loss and …

Industrial Applications of Machine Learning shows how machine learning can be applied to
address real-world problems in the fourth industrial revolution, and provides the required …

No comprehensive review of Bayesian networks (BNs) in healthcare has been published in
the past, making it difficult to organize the research contributions in the present and identify …

While population-scale neuroimaging studies offer the promise of discovery and
characterisation of subtle risk factors, massive sample sizes increase the power for both …

Fishing is considered one of the most dangerous occupations globally. Small-scale
fisheries, which make up about 90% of the entire industry worldwide, are done using small …

Driving behavior is generally considered to be one of the most important factors in crash
occurrence. This paper aims to evaluate the benefits of utilizing context-relevant information …