AI and Neurology.

Julian Bösel, Rohan Mathur, Lin Cheng, Marianna S Varelas, Markus A Hobert, José I Suarez
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引用次数: 0

Abstract

Background: Artificial Intelligence is influencing medicine on all levels. Neurology, one of the most complex and progressive medical disciplines, is no exception. No longer limited to neuroimaging, where data-driven approaches were initiated, machine and deep learning methodologies are taking neurologic diagnostics, prognostication, predictions, decision making and even therapy to very promising potentials.

Main body: In this review, the basic principles of different types of Artificial Intelligence and the options to apply them to neurology are summarized. Examples of noteworthy studies on such applications are presented from the fields of acute and intensive care neurology, stroke, epilepsy, and movement disorders. Finally, these potentials are matched with risks and challenges jeopardizing ethics, safety and equality, that need to be heeded by neurologists welcoming Artificial Intelligence to their field of expertise.

Conclusion: Artificial intelligence is and will be changing neurology. Studies need to be taken to the prospective level and algorithms undergo federated learning to reach generalizability. Neurologists need to master not only the benefits but also the risks in safety, ethics and equity of such data-driven form of medicine.

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来源期刊
CiteScore
7.40
自引率
0.00%
发文量
0
审稿时长
14 weeks
期刊最新文献
AI and Neurology. Neurological Research and Practice - the premier journal of the German Society of Neurology: recent development and future perspectives. Severe subacute combined degeneration of the spinal cord resulting from nitrous oxide (N2O) abuse: a case series. Association of oral anticoagulants with risk of brain haemorrhage expansion compared to no-anticoagulation. Shared prognostic information in amyotrophic lateral sclerosis - systematic assessment of the patients' perception of neurofilament light chain and the ALS functional rating scale.
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