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山东大学学报 (医学版) ›› 2020, Vol. 58 ›› Issue (11): 1-10.doi: 10.6040/j.issn.1671-7554.0.2020.1181

• 眼科人工智能新进展专题 •    下一篇

人工智能在眼科真实临床场景的应用:机遇和挑战

何明光1,*(),刘驰1,2,李治玺1   

  1. 1. 中山大学中山眼科中心,眼科学国家重点实验室, 广东 广州 510060
    2. 悉尼科技大学计算机学院, 澳大利亚 悉尼 2007
  • 收稿日期:2020-08-17 出版日期:2020-11-10 发布日期:2020-11-04
  • 通讯作者: 何明光 E-mail:mingguang_he@yahoo.com
  • 作者简介:何明光,中山大学中山眼科中心二级教授,博士研究生导师,亚太眼科学会副秘书长和理事,亚太远程眼科学会主席,中华医学会眼科分会防盲和流行病学学组组长。国家杰出青年基金获得者、国家“万人计划”领军人才、广东特支计划杰出人才(“南粤百杰”)。研究领域主要包括眼科疾病的临床和遗传流行病学研究、近视防控、双生子研究、图像技术研究、人工智能和大数据研究。以第一或通讯作者在《JAMA》《Lancet》《Diabetes care》《Ophthalmology》等期刊发表原创论文370篇,连续6年被评为中国医学领域高被引学者
  • 基金资助:
    国家重点研发计划(2018YFC0116500);国家自然科学基金眼科国家重点实验室基础研究(81420108008);广东省科技计划项目(2013B20400003)

Applying artificial intelligence in ophthalmic real-world practice: opportunities and challenges

Mingguang HE1,*(),Chi LIU1,2,Zhixi LI1   

  1. 1. State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510060, Guangdong, China
    2. School of Computer Science, University of Technology Sydney, Sydney 2007, NSW, Australia
  • Received:2020-08-17 Online:2020-11-10 Published:2020-11-04
  • Contact: Mingguang HE E-mail:mingguang_he@yahoo.com

摘要:

人工智能在包括眼科在内的许多临床学科中已经从实验阶段快速发展到实施阶段。以数据驱动的深度学习技术为基于眼科影像数据的自动化诊断技术创造了前所未有的机会,显著提高眼科医疗系统的可及性、效率和成本效益。虽然这项技术在不久的将来,必然会对临床流程和实践模式产生深远影响,但将其转化为真实世界临床实践仍然具有挑战性。本文将在介绍这一领域的一些进展的基础上,重点总结人工智能在眼科真实医疗场景投放中的机遇和挑战,指出了其中可能会存在的一系列潜在问题,例如诊断偏差、医学伦理和法律问题、临床评价和产品注册规范性等,以期促进该技术与临床实践的结合,进一步提升眼科人工智能的应用价值。

关键词: 人工智能, 眼科, 真实世界投放, 临床实践

Abstract:

Artificial intelligence has rapidly evolved from the experimental phase to the implementation phase in many clinical disciplines, including ophthalmology. The data-driven deep learning technology has created unprecedented opportunities for major breakthroughs in the imaging data-based automated diagnoses in ophthalmology, significantly improving the accessibility, efficiency, and cost-effectiveness of eye care systems. Although this technology will have a profound impact on clinical flow and practice patterns sooner or later, translating such a technology into clinical practice is challenging. With comprehensively going through the latest progress in this research domain, this article highlights the opportunities and challenges of the real-world deployment of artificial intelligence in ophthalmology, and figures out the potential problems that may arise during the transition, such as diagnosis bias, clinical evaluation, medical accountability, as well as ethical and legal issues. The discovery could facilitate the integration of artificial intelligence into routine clinical practice and further improve the relevant applications.

Key words: Artificial intelligence, Ophthalmology, Real-world deployment, Clinical practice

中图分类号: 

  • R770.4

图1

AI分类机会筛查模型"

图2

AI用做初始分类策略以最大化人工分级的效率"

图3

3种临床途径整合模式:分类、替换和附加"

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