American Society of Retina Specialists Artificial Intelligence Task Force Report

被引：0

作者：

Talcott, Katherine E. ^{[1
,2
]}

Baxter, Sally L. ^{[3
,4
,5
]}

Chen, Dinah K. ^{[6
,7
]}

Korot, Edward ^{[8
,9
]}

Lee, Aaron ^{[10
]}

Kim, Judy E. ^{[11
]}

Modi, Yasha ^{[6
]}

Moshfeghi, Darius M. ^{[9
]}

Singh, Rishi P. ^{[1
,2
,12
]}

机构：

[1] Cleveland Clin Fdn, Cole Eye Inst, Ctr Ophthalm Bioinformat, Cleveland, OH USA

[2] Cleveland Clin, Lerner Coll Med, Cleveland, OH USA

[3] Univ Calif San Diego, Div Ophthalmol Informat & Data Sci, Viterbi Family Dept Ophthalmol, La Jolla, CA USA

[4] Univ Calif San Diego, Shiley Eye Inst, La Jolla, CA USA

[5] Univ Calif San Diego, Dept Med, Div Biomed Informat, La Jolla, CA USA

[6] NYU, NYU Grossman Sch Med, Dept Ophthalmol, New York, NY USA

[7] Genentech Roche, South San Francisco, CA USA

[8] Retina Specialists Michigan, Grand Rapids, MI USA

[9] Stanford Univ, Byers Eye Inst, Horngren Family Vitreoretinal Ctr, Dept Ophthalmol,Sch Med, Palo Alto, CA USA

[10] Univ Washington, Roger & Angie Karalis Johnson Retina Ctr, Sch Med, Dept Ophthalmol, Seattle, WA USA

[11] Med Coll Wisconsin, Dept Ophthalmol & Visual Sci, Milwaukee, WI USA

[12] Cleveland Clin Martin Hlth, 200 SE Hosp Ave,POB 9010, Stuart, FL 34995 USA

来源：

JOURNAL OF VITREORETINAL DISEASES | 2024年 / 8卷 / 04期

关键词：

artificial intelligence; deep learning; optical coherence tomography; fundus photographs; diabetic retinopathy; bias; commercialization; data sources; education; retina; DIABETIC-RETINOPATHY; AUTOMATED DETECTION; DEEP; VALIDATION; IMAGES; CLASSIFICATION; OPHTHALMOLOGY; PREDICTION; ALGORITHM; DISEASES;

D O I：

10.1177/24741264241247602

中图分类号：

R77 [眼科学];

学科分类号：

100212 ;

摘要：

Since the Artificial Intelligence Committee of the American Society of Retina Specialists developed the initial task force report in 2020, the artificial intelligence (AI) field has seen further adoption of US Food and Drug Administration-approved AI platforms and significant development of AI for various retinal conditions. With expansion of this technology comes further areas of challenges, including the data sources used in AI, the democracy of AI, commercialization, bias, and the need for provider education on the technology of AI. The overall focus of this committee report is to explore these recent issues as they relate to the continued development of AI and its integration into ophthalmology and retinal practice.

引用

页码：373 / 380

页数：8

共 76 条

[1]

A-AMI, AMIA 10x10 Virtual Courses

[2] Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices [J].

Abramoff, Michael D. ;

Lavin, Philip T. ;

Birch, Michele ;

Shah, Nilay ;

Folk, James C. .

NPJ DIGITAL MEDICINE, 2018, 1

[3] Improved Automated Detection of Diabetic Retinopathy on a Publicly Available Dataset Through Integration of Deep Learning [J].

Abramoff, Michael David ;

Lou, Yiyue ;

Erginay, Ali ;

Clarida, Warren ;

Amelon, Ryan ;

Folk, James C. ;

Niemeijer, Meindert .

INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2016, 57 (13) :5200-5206

[4]

ACGME International, Clinical informatics

[5]

AI-LAB, Home

[6]

AIM-AHEAD, AIM-AHEAD

[7]

American Academy of Ophthalmology, Artificial Intelligence

[8]

American Academy of Ophthalmology, 2021, Medicare carrier underprices new AI screening code, breaking from peers

[9]

American Academy of Ophthalmology, 2022-2023 basic and clinical science course complete set

[10] Predictive modeling of proliferative vitreoretinopathy using automated machine learning by ophthalmologists without coding experience [J].

Antaki, Fares ;

Kahwati, Ghofril ;

Sebag, Julia ;

Coussa, Razek Georges ;

Fanous, Anthony ;

Duval, Renaud ;

Sebag, Mikael .

SCIENTIFIC REPORTS, 2020, 10 (01)

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