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医生与机器的自动化:医学人工智能分类(ADAM框架)

The automation of doctors and machines: A classification for AI in medicine (ADAM framework).

作者信息

Kazzazi Fawz

机构信息

Mason Institute for Medicine, Life Sciences and Law, Edinburgh, UK.

出版信息

Future Healthc J. 2021 Jul;8(2):e257-e262. doi: 10.7861/fhj.2020-0189.

Abstract

The advances in artificial intelligence (AI) provide an opportunity to expand the frontier of medicine to improve diagnosis, efficiency and management. By extension of being able to perform any task that a human could, a machine that meets the requirements of artificial general intelligence ('strong' AI; AGI) possesses the basic necessities to perform as, or at least qualify to become, a doctor. In this emerging field, this article explores the distinctions between doctors and AGI, and the prerequisites for AGI performing as clinicians. In doing so, it necessitates the requirement for a classification of medical AI and prepares for the development of AGI. With its imminent arrival, it is beneficial to create a framework from which leading institutions can define specific criteria for AGI.

摘要

人工智能(AI)的进步为拓展医学前沿以改善诊断、效率和管理提供了契机。通过能够执行人类所能执行的任何任务,一台符合通用人工智能(“强”AI;AGI)要求的机器具备了成为医生或至少有资格成为医生的基本条件。在这个新兴领域,本文探讨了医生与AGI之间的区别,以及AGI作为临床医生的先决条件。这样做需要对医学AI进行分类,并为AGI的发展做好准备。随着AGI的即将到来,创建一个框架以便领先机构能够为AGI定义具体标准是有益的。

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