AI and Neurology.

Q2 Medicine
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.

人工智能和神经学。
背景:人工智能正在影响医学的各个层面。神经病学作为最复杂、最先进的医学学科之一,也不例外。机器和深度学习方法不再局限于数据驱动方法的神经成像领域,它们正在将神经系统诊断、预测、预测、决策甚至治疗带入非常有前景的领域。主体:本文综述了不同类型人工智能的基本原理及其在神经病学中的应用。在急性重症监护神经学、中风、癫痫和运动障碍等领域提出了值得注意的应用研究的例子。最后,这些潜力与危及伦理、安全和平等的风险和挑战相匹配,这是神经学家欢迎人工智能进入其专业领域所需要注意的。结论:人工智能正在并将改变神经学。研究需要采取前瞻性水平和算法进行联合学习,以达到泛化。神经科医生不仅需要掌握这种数据驱动的医学形式的好处,还需要掌握安全、伦理和公平方面的风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.40
自引率
0.00%
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审稿时长
14 weeks
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