Pedersen Mangor, Verspoor Karin, Jenkinson Mark, Law Meng, Abbott David F, Jackson Graeme D
The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Heidelberg, VIC 3084, Australia.
Department of Psychology, Auckland University of Technology (AUT), Auckland, 0627, New Zealand.
Brain Commun. 2020 Jul 9;2(2):fcaa096. doi: 10.1093/braincomms/fcaa096. eCollection 2020.
Artificial intelligence is one of the most exciting methodological shifts in our era. It holds the potential to transform healthcare as we know it, to a system where humans and machines work together to provide better treatment for our patients. It is now clear that cutting edge artificial intelligence models in conjunction with high-quality clinical data will lead to improved prognostic and diagnostic models in neurological disease, facilitating expert-level clinical decision tools across healthcare settings. Despite the clinical promise of artificial intelligence, machine and deep-learning algorithms are not a one-size-fits-all solution for all types of clinical data and questions. In this article, we provide an overview of the core concepts of artificial intelligence, particularly contemporary deep-learning methods, to give clinician and neuroscience researchers an appreciation of how artificial intelligence can be harnessed to support clinical decisions. We clarify and emphasize the data quality and the human expertise needed to build robust clinical artificial intelligence models in neurology. As artificial intelligence is a rapidly evolving field, we take the opportunity to iterate important ethical principles to guide the field of medicine is it moves into an artificial intelligence enhanced future.
人工智能是我们这个时代最令人兴奋的方法变革之一。它有潜力将我们所知的医疗保健转变为一个人类与机器共同协作，为患者提供更好治疗的系统。现在很明显，前沿的人工智能模型与高质量的临床数据相结合，将改善神经疾病的预后和诊断模型，促进跨医疗环境的专家级临床决策工具的发展。尽管人工智能具有临床前景，但机器和深度学习算法并非适用于所有类型临床数据和问题的万能解决方案。在本文中，我们概述了人工智能的核心概念，特别是当代深度学习方法，以使临床医生和神经科学研究人员了解如何利用人工智能来支持临床决策。我们阐明并强调了构建强大的神经学临床人工智能模型所需的数据质量和专业知识。由于人工智能是一个快速发展的领域，我们借此机会重申重要的伦理原则，以指导医学领域迈向人工智能增强的未来。
