DANESE, Carla; KALE, Aditya U; ASLAM, Tariq; LANZETTA, Paolo; BARRATT, Jane; CHOU, Yu-Bai; ELDEM, Bora; ETER, Nicole; GALE, Richard; KOROBELNIK, Jean-Francois; KOZAK, Igor; LI, Xiaorong; LI, Xiaoxin; LOEWENSTEIN, Anat; RUAMVIBOONSUK, Paisan; SAKAMOTO, Taiji; TING, Daniel S W; VAN WIJNGAARDEN, Peter; WALDSTEIN, Sebastian M; WONG, David; WU, Lihteh; ZAPATA, Miguel A; ZARRANZ-VENTURA, Javier

doi:10.1097/ICU.0000000000000980

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Ce document a été publié dans

Current Opinion in Ophthalmology. 2023-09-01, vol. 34, n° 5, p. 396-402

Résumé en anglais

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. 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. 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.< Réduire

Mots clés en anglais

Humans

Artificial Intelligence

Consensus

Retinal Diseases

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https://oskar-bordeaux.fr/handle/20.500.12278/184763

DOI

http://dx.doi.org/10.1097/ICU.0000000000000980

Unités de recherche

Bordeaux Population Health Research Center (BPH) - UMR 1219

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

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Résumé en anglais

Mots clés en anglais

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