The impact of artificial intelligence on retinal disease management: Vision Academy retinal expert consensus

Author:

Danese Carla12,Kale Aditya U.3,Aslam Tariq4,Lanzetta Paolo15,Barratt Jane6,Chou Yu-Bai78,Eldem Bora9,Eter Nicole10,Gale Richard11,Korobelnik Jean-François1213,Kozak Igor14,Li Xiaorong15,Li Xiaoxin16,Loewenstein Anat17,Ruamviboonsuk Paisan18,Sakamoto Taiji19,Ting Daniel S.W.20,van Wijngaarden Peter2122,Waldstein Sebastian M.23,Wong David24,Wu Lihteh25,Zapata Miguel A.26,Zarranz-Ventura Javier27

Affiliation:

1. Department of Medicine – Ophthalmology, University of Udine, Udine, Italy

2. Department of Ophthalmology, AP-HP Hôpital Lariboisière, Université Paris Cité, Paris, France

3. Academic Unit of Ophthalmology, Institute of Inflammation & Ageing, College of Medical and Dental Sciences, University of Birmingham, Birmingham

4. Division of Pharmacy and Optometry, Faculty of Biology, Medicine and Health, University of Manchester School of Health Sciences, Manchester, UK

5. Istituto Europeo di Microchirurgia Oculare, Udine, Italy

6. International Federation on Ageing, Toronto, Canada

7. Department of Ophthalmology, Taipei Veterans General Hospital

8. School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan

9. Department of Ophthalmology, Hacettepe University, Ankara, Turkey

10. Department of Ophthalmology, University of Münster Medical Center, Münster, Germany

11. Department of Ophthalmology, York Teaching Hospital NHS Foundation Trust, York, UK

12. Service d’ophtalmologie, CHU Bordeaux

13. University of Bordeaux, INSERM, BPH, UMR1219, F-33000 Bordeaux, France

14. Moorfields Eye Hospital Centre, Abu Dhabi, UAE

15. Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin

16. Xiamen Eye Center, Xiamen University, Xiamen, China

17. Division of Ophthalmology, Tel Aviv Sourasky Medical Center, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel

18. Department of Ophthalmology, College of Medicine, Rangsit University, Rajavithi Hospital, Bangkok, Thailand

19. Department of Ophthalmology, Kagoshima University, Kagoshima, Japan

20. Singapore National Eye Center, Duke-NUS Medical School, Singapore

21. Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, Australia

22. Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia

23. Department of Ophthalmology, Landesklinikum Mistelbach-Gänserndorf, Mistelbach, Austria

24. Unity Health Toronto – St. Michael's Hospital, University of Toronto, Toronto, Canada

25. Macula, Vitreous and Retina Associates of Costa Rica, San José, Costa Rica

26. Ophthalmology Department, Hospital Vall d’Hebron

27. Hospital Clínic de Barcelona, University of Barcelona, Barcelona, Spain

Abstract

Purpose of reviewThe aim of this review is to define the “state-of-the-art” in artificial intelligence (AI)-enabled devices that support the management of retinal conditions and to provide Vision Academy recommendations on the topic.Recent findingsMost of the AI models described in the literature have not been approved for disease management purposes by regulatory authorities. These new technologies are promising as they may be able to provide personalized treatments as well as a personalized risk score for various retinal diseases. However, several issues still need to be addressed, such as the lack of a common regulatory pathway and a lack of clarity regarding the applicability of AI-enabled medical devices in different populations.SummaryIt is likely that current clinical practice will need to change following the application of AI-enabled medical devices. These devices are likely to have an impact on the management of retinal disease. However, a consensus needs to be reached to ensure they are safe and effective for the overall population.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Ophthalmology,General Medicine

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3