IMR Press / JIN / Special Issues / 1631256435911

Big Data Analytics and Intelligent Techniques for Neuroscience

Submission deadline: 30 June 2022
Special Issue Editor
Ahmed Farouk, PhD
Department of Physics and Computer Science, Faculty of Science, Wilfrid Laurier University, N2L 3C5 Waterloo, ON, Canada
Interests: Big data analytics; Artificial intelligence; Neuroscience; Health informatics; Signal processing; Radiology nuclear medicine and imaging; Radiological and ultrasound technology; Clinical neurology; Neurology; Surgery; Critical care and Intensive care medicine
Special Issue Information

Dear Colleagues, 

In recent years, with the rapid upscaling of biological data volumes, data-driven computational methods have been increasingly needed for their handling and analysis. In particular, neuroscientific, biological and medical technologies have generated explosive volumes of data via methods such as medical imaging, electroencephalography, genomics and protein sequencing. Learning from these data furthers the understanding of human health and disease. Accordingly, computational and machine learning techniques have emerged as an “intelligent” method to gain insight from data in many areas of healthcare within both academia and industry. To expand the scope and ease of applicability of machine learning, it is highly desirable to make learning algorithms less dependent on handcrafted feature engineering, in order to improve the speed of construction of novel applications and, more importantly, to make progress toward artificial intelligence (AI). Neuroscience as a Service (NaaS) may enable neuroscience-related healthcare and scientific research to be conducted in natural settings rather than equipment rooms in laboratories and medical centers. NaaS is somewhat analogous to the concept of Software as a Service (SaaS)—decentralized cloud-based computing, where a third-party provider hosts a given application. Stakeholders access the application through the internet, enabling them to focus on their domain expertise rather than attempting to run complex data centers, technology stacks and other network infrastructures. By leveraging the interdisciplinary domains of state-of-the-art AI, machine learning, neuroscience, engineering, healthcare, and physics, NaaS can lead to the creation of innovative platforms that may accelerate neuroscientific discovery and application. Recent advances in multimedia in emerging technologies have allowed their integration with state-of-the-art methodologies, systems for the creation of innovative health care services. This special issue includes research studies on the advances in the field of computing and artificial intelligence.  We describe the contribution of state-of-the-art methods in the latest research and development and challenges in the field of neuroscience, including neuroanatomy, neuroimaging, modeling, neurocomputation, neural networks, molecular neurobiology, cyto-neurology, neurophysiology, neuropathology, neuroimmunology, neuropharmacology, behavioral neuroscience, developmental neurosciences, neuro-oncology, cognitive neuroscience, system neuroscience, computational neurosciences, neuroevolution, neuropsychology, clinical neurology, neurosurgery, brain disorders, neurovascular diseases, stroke, neuroendocrinology, neurotoxicology, and other areas.
Topics include but not restricted to:
• Emerging multimedia processing in neuroscience as a service for health care and neuroscience
• Emerging applications for managing neuroscience as a service for medical media data
• The innovative use of artificial intelligence techniques, algorithms and methods to monitor and track casualties and contacts in outbreaks of epidemic diseases and beyond
• Case study along with design or development of innovative multimedia smart healthcare materials, tools, and devices
• Mobile multimedia emerging technologies for health care and neuroscience
• Emerging technologies-based health monitoring and neuroscience
• Emerging technologies -based remote display protocol for health care
• ML/DL-based patient condition screening, visualization, and monitoring
• AI-empowered multimedia healthcare data analytics in infectious diseases and beyond
• Emerging media cloud protocols, surveys, applications and new research approaches
• Emerging technologies-based model for automatic detection of mental disorder at home
• Usage of neuroscience as a service in improving customer services
• Use of neuroscience as a service for business improvement
• Neural-based mathematical formulation of information and data using machine and deep learning
• Human perception, cognition, and decision making through neural networks

Assoc. Prof. Ahmed Farouk

Guest Editor

Big data analytics
Artificial intelligence
Health informatics
Signal processing
Radiology nuclear medicine and imaging
Radiological and ultrasound technology
Clinical neurology
Critical care and intensive care medicine
Manuscript Submission Information

Manuscripts should be submitted via our online editorial system at by registering and logging in to this website. Once you are registered, click here to start your submission. Manuscripts can be submitted now or up until the deadline. All papers will go through peer-review process. Accepted papers will be published in the journal (as soon as accepted) and meanwhile listed together on the special issue website. Research articles, reviews as well as short communications are preferred. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office to announce on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts will be thoroughly refereed through a double-blind peer-review process. Please visit the Instruction for Authors page before submitting a manuscript. The Article Processing Charge (APC) in this open access journal is 1900 USD. Submitted manuscripts should be well formatted in good English.

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