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

Carla Danese, Aditya U Kale, Tariq Aslam, Paolo Lanzetta, Jane Barratt, Yu-Bai Chou, Bora Eldem, Nicole Eter, Richard Gale, Jean-François Korobelnik, Igor Kozak, Xiaorong Li, Xiaoxin Li, Anat Loewenstein, Paisan Ruamviboonsuk, Taiji Sakamoto, Daniel S W Ting, Peter van Wijngaarden, Sebastian M Waldstein, David WongLihteh Wu, Miguel A Zapata, Javier Zarranz-Ventura

Research output: Contribution to journalReview articlepeer-review


PURPOSE OF REVIEW: The 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 FINDINGS: Most 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.

SUMMARY: It 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.

Original languageEnglish
Pages (from-to)396-402
Number of pages7
JournalCurrent opinion in ophthalmology
Issue number5
Publication statusPublished - 1 Sept 2023


  • artificial intelligence
  • disease management
  • retina


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