Current status and practical considerations of artificial intelligence use in screening and diagnosing retinal diseases: Vision Academy retinal expert consensus

Author:

Chou Yu-Bai12,Kale Aditya U.3,Lanzetta Paolo45,Aslam Tariq6,Barratt Jane7,Danese Carla48,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 Ophthalmology, Taipei Veterans General Hospital

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

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

4. Department of Medicine – Ophthalmology, University of Udine

5. Istituto Europeo di Microchirurgia Oculare, Udine, Italy

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

7. International Federation on Ageing, Toronto, Canada

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

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 review The application of artificial intelligence (AI) technologies in screening and diagnosing retinal diseases may play an important role in telemedicine and has potential to shape modern healthcare ecosystems, including within ophthalmology. Recent findings In this article, we examine the latest publications relevant to AI in retinal disease and discuss the currently available algorithms. We summarize four key requirements underlining the successful application of AI algorithms in real-world practice: processing massive data; practicability of an AI model in ophthalmology; policy compliance and the regulatory environment; and balancing profit and cost when developing and maintaining AI models. Summary The Vision Academy recognizes the advantages and disadvantages of AI-based technologies and gives insightful recommendations for future directions.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Ophthalmology,General Medicine

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