Lavigne Maxime, Mussa Fatima, Creatore Maria I, Hoffman Steven J, Buckeridge David L
1 Surveillance Lab, McGill Clinical and Health Informatics, McGill University, Montreal, Quebec, Canada.
2 Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada.
Healthc Manage Forum. 2019 Jul;32(4):173-177. doi: 10.1177/0840470419848428. Epub 2019 May 19.
The burgeoning field of Artificial Intelligence (AI) has the potential to profoundly impact the public's health. Yet, to make the most of this opportunity, decision-makers must understand AI concepts. In this article, we describe approaches and fields within AI and illustrate through examples how they can contribute to informed decisions, with a focus on population health applications. We first introduce core concepts needed to understand modern uses of AI and then describe its sub-fields. Finally, we examine four sub-fields of AI most relevant to population health along with examples of available tools and frameworks. Artificial intelligence is a broad and complex field, but the tools that enable the use of AI techniques are becoming more accessible, less expensive, and easier to use than ever before. Applications of AI have the potential to assist clinicians, health system managers, policy-makers, and public health practitioners in making more precise, and potentially more effective, decisions.
新兴的人工智能（AI）领域有可能对公众健康产生深远影响。然而，为了充分利用这一机遇，决策者必须理解人工智能的概念。在本文中，我们描述了人工智能领域内的方法和领域，并通过实例说明它们如何有助于做出明智的决策，重点是人群健康应用。我们首先介绍理解人工智能现代应用所需的核心概念，然后描述其各个子领域。最后，我们研究了与人群健康最相关的人工智能的四个子领域，并列举了可用工具和框架的示例。人工智能是一个广泛而复杂的领域，但使人工智能技术得以应用的工具正变得比以往任何时候都更容易获取、成本更低且更易于使用。人工智能的应用有潜力帮助临床医生、卫生系统管理人员、政策制定者和公共卫生从业者做出更精确、可能更有效的决策。
