Cognitive Computing and Artificial Intelligence to Address Real-Time Tele-Neurology and Neurophysiology

Topic Information

Dear Colleagues,

Cognitive computing is a field that uses data science tools and technologies to process information. It involves self-directed learning blended with artificial intelligence and data mining to experiment with solving convoluted real-world problems with reduced human intervention. Neuroscience informatics and cognitive computing tests analyze brain tasks and functioning in different scenarios. This is a flexible field which involves multidisciplinary concepts from computers, electrical engineering and physics to understand how the brain system processes information.

Neurophysiological monitoring and testing are used in surgical procedures that place the nervous system at risk or require identification, mapping or testing of neurosystems. Monitoring neurostructural functions at risk provides an early warning system which can help to prevent neurological complications. This, according to RTNA (Real-Time Neuromonitoring Associates), involves real-time monitoring of over 45,000 orthopedic, neurosurgical, cardiovascular and otologic surgeries annually from accredited physicians in over 700 hospitals and over 1300 healthcare facilities. This Topic will focus on tele-neurology and neurophysiology and invites submissions of original research/reviews on neuroscience informatics from both organizations and individuals.

The aim of this Topic is to blend cognition, artificial intelligence, and neuroscience information processing together to address real-time tele-neurology and neurophysiology. This issue covers but is not limited to the topics below.

Topics to be covered

• Building computational models and frameworks for tele-neurology and neurophysiology
• Testing and behavioral analysis of brain activities and neuromonitoring
• Security concerns in building computational model for real-time neuromonitoring
• Role of artificial intelligence in cognitive learning in real-time neuromonitoring
• Use of cognition to brain health analysis and testing
• Machine-learning-/deep-learning-based monitoring, visualization, and interpretation
• Comparison and analysis on brain health using AI
• Opinion mining
• Study of semantic analysis
• Applications in other industries and organizations

Dr. Mohammad Shabaz
Topic Editor

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
AI ai	3.1	7.2	2020	18.9 Days	CHF 1600
Clinical and Translational Neuroscience ctn	-	-	2017	33.9 Days	CHF 1000
Medicina medicina	2.4	3.3	1920	17.1 Days	CHF 2200
Robotics robotics	2.9	6.7	2012	21 Days	CHF 1800

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