Artificial intelligence as an emerging technology in the current care of neurological disorders

  • Urvish K. PatelEmail author
  • Arsalan Anwar
  • Sidra Saleem
  • Preeti Malik
  • Bakhtiar Rasul
  • Karan Patel
  • Robert Yao
  • Ashok Seshadri
  • Mohammed Yousufuddin
  • Kogulavadanan Arumaithurai



Artificial intelligence (AI) has influenced all aspects of human life and neurology is no exception to this growing trend. The aim of this paper is to guide medical practitioners on the relevant aspects of artificial intelligence, i.e., machine learning, and deep learning, to review the development of technological advancement equipped with AI, and to elucidate how machine learning can revolutionize the management of neurological diseases. This review focuses on unsupervised aspects of machine learning, and how these aspects could be applied to precision neurology to improve patient outcomes. We have mentioned various forms of available AI, prior research, outcomes, benefits and limitations of AI, effective accessibility and future of AI, keeping the current burden of neurological disorders in mind.


The smart device system to monitor tremors and to recognize its phenotypes for better outcomes of deep brain stimulation, applications evaluating fine motor functions, AI integrated electroencephalogram learning to diagnose epilepsy and psychological non-epileptic seizure, predict outcome of seizure surgeries, recognize patterns of autonomic instability to prevent sudden unexpected death in epilepsy (SUDEP), identify the pattern of complex algorithm in neuroimaging classifying cognitive impairment, differentiating and classifying concussion phenotypes, smartwatches monitoring atrial fibrillation to prevent strokes, and prediction of prognosis in dementia are unique examples of experimental utilizations of AI in the field of neurology. Though there are obvious limitations of AI, the general consensus among several nationwide studies is that this new technology has the ability to improve the prognosis of neurological disorders and as a result should become a staple in the medical community.


AI not only helps to analyze medical data in disease prevention, diagnosis, patient monitoring, and development of new protocols, but can also assist clinicians in dealing with voluminous data in a more accurate and efficient manner.


Artificial intelligence Machine learning Deep learning Neurological disorders Stroke Epilepsy SUDEP Movement disorders Concussion Alzheimer’s disease Technology 


Author contributions

Conceptualization, UP; methodology: none; formal analysis and investigation, UP, AA, SS; writing—original draft preparation, KA, AA, SS, UP; writing—review and editing, PM, KP, RY, AS, MY, BR; supervision, KA; project administration, UP; resources, UP; funding acquisition, none.


The study had no internal or external funding source.

Compliance with ethical standards

Conflicts of interest

The authors report no disclosures relevant to the manuscript. The authors declare that there is no conflict of interest. Robert Yao is the founder and CEO of EpiFinder, Inc.

Informed consent

This review article does not have direct or indirect involvement of humans or animals, so permission from IRB or ethics committee was not applicable or required.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Urvish K. Patel
    • 1
    Email author
  • Arsalan Anwar
    • 2
  • Sidra Saleem
    • 3
  • Preeti Malik
    • 4
  • Bakhtiar Rasul
    • 4
  • Karan Patel
    • 5
  • Robert Yao
    • 6
  • Ashok Seshadri
    • 7
  • Mohammed Yousufuddin
    • 8
  • Kogulavadanan Arumaithurai
    • 9
  1. 1.Department of Neurology and Public HealthIcahn School of Medicine at Mount SinaiNew YorkUSA
  2. 2.Department of NeurologyUH Cleveland Medical CenterClevelandUSA
  3. 3.Department of NeurologyUniversity of ToledoToledoUSA
  4. 4.Department of Public HealthIcahn School of Medicine at Mount SinaiNew YorkUSA
  5. 5.Department of NeuroscienceJohns Hopkins UniversityBaltimoreUSA
  6. 6.Department of Biomedical InformaticsArizona State University and Mayo Clinic ArizonaScottsdaleUSA
  7. 7.Department of PsychiatryMayo Clinic Health SystemRochesterUSA
  8. 8.Department of Internal MedicineMayo Clinic Health SystemAustinUSA
  9. 9.Department of NeurologyMayo Clinic Health SystemAustinUSA

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