Lehigh Valley Fleming Neuroscience Institute, 1250 S Cedar Crest Blvd., Allentown, PA 18103, USA.
Cleveland Clinic Information Technology Division, 9500 Euclid Ave. Cleveland, OH 44195, USA.
J Neurol Sci. 2023 Dec 15;455:122799. doi: 10.1016/j.jns.2023.122799. Epub 2023 Nov 14.
Machine learning techniques for clinical applications are evolving, and the potential impact this will have on clinical neurology is important to recognize. By providing a broad overview on this growing paradigm of clinical tools, this article aims to help healthcare professionals in neurology prepare to navigate both the opportunities and challenges brought on through continued advancements in machine learning. This narrative review first elaborates on how machine learning models are organized and implemented. Machine learning tools are then classified by clinical application, with examples of uses within neurology described in more detail. Finally, this article addresses limitations and considerations regarding clinical machine learning applications in neurology.
机器学习技术在临床应用中的发展日新月异,认识到这将对临床神经病学产生的潜在影响非常重要。本文通过广泛概述这一不断发展的临床工具范例,旨在帮助神经病学领域的医疗保健专业人员做好准备,迎接机器学习持续进步带来的机遇和挑战。本文首先详细阐述了机器学习模型的组织和实施方式。然后根据临床应用对机器学习工具进行分类,并详细描述了在神经病学中的应用实例。最后,本文还讨论了神经病学中临床机器学习应用的局限性和注意事项。