Gunasekeran DV, Zheng F, Lim GYS, Chong CCY, Zhang S, Ng WY, Keel S, Xiang Y, Park KH, Park SJ, Chandra A, Wu L, Campbel JP, Lee AY, Keane PA, Denniston A, Lam DSC, Fung AT, Chan PRV, Sadda SR, Loewenstein A, Grzybowski A, Fong KCS, Wu WC, Bachmann LM, Zhang X, Yam JC, Cheung CY, Pongsachareonnont P, Ruamviboonsuk P, Raman R, Sakamoto T, Habash R, Girard M, Milea D, Ang M, Tan GSW, Schmetterer L, Cheng CY, Lamoureux E, Lin H, van Wijngaarden P, Wong TY, and Ting DSW
Background: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract., Methods: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning., Results: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10-12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63-0.83., Conclusion: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology., Competing Interests: DG reports appointment as Physician Leader (Telemedicine) for Raffles Medical Group (SGX:$BSL.SI) and investments in digital health start-ups AskDr, Doctorbell (acquired by MaNaDr), Shyfts, and VISRE. JC reports appointment as a consultant to Boston AI labs. AYL reports grants from Santen, personal fees from Genentech, US FDA, Johnson and Johnson, grants from Carl Zeiss Meditec, personal fees from Topcon, Gyroscope, non-financial support from Microsoft, grants from Regeneron, outside the submitted work; This article does not reflect the views of the US FDA. PK reports having acted as a consultant for DeepMind, Roche, Novartis, Apellis, and BitFount and is an equity owner in Big Picture Medical. He has received speaker fees from Heidelberg Engineering, Topcon, Allergan, and Bayer. AF reports honoraria, advisory board and grant funding from Alcon, Bayer, Novartis, Allergan, Roche, and Syneos Health. AL reports grants from Roche and Novartis, and appointment as a consultant to NotalVision, Allergan, Bayer, WebMD, and Beyeonics. AG reports appointment to provide lectures for Pfizer, Thea, and Polpharma. TS reports appointment as a consultant & advisory board for Bayer Yakuhin, Boehringer-Ingelheim, Novartis, Chugai, Senju, and Santen. DM reports funding support from the Singapore National Medical Research Council (NMRC-CIRG18Nov-0013), and the Duke-NUS Medical School, Singapore (ACP 05/FY2019/P2/06-A60). DM also reports appointment as consultant and Advisory Board Member of Optomed, Finland. TW reports appointment as the deputy group chief executive officer (research and education) of Singapore Health Services, a consultant & advisory board for Allergan, Bayer, Boehringer-Ingelheim, Genentech, Merck, Novartis, Oxurion (formerly ThromboGenics), Roche, and co-founder of Plano. DT reports funding from the following grants for research about AI in healthcare: National Medical Research Council, Singapore (NMRC/HSRG/0087/2018; MOH-000655-00), National Health Innovation Center, Singapore (NHIC-COV19-2005017), SingHealth Fund Limited Foundation (SHF/HSR113/2017), Duke-NUS Medical School, Singapore (Duke-NUS/RSF/2021/0018; 05/FY2020/EX/15-A58), and Agency for Science, Technology and Research (ASTAR), Singapore (A20H4g2141 and A20H4g2141). DT, GL, and TW also report being the co-inventors of a deep learning system for retinal diseases and co-founders of related start-up Eyris; potential conflicts of interests are managed according to institutional policies of the Singapore Health System (SingHealth) and the National University of Singapore (NUS). The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Gunasekeran, Zheng, Lim, Chong, Zhang, Ng, Keel, Xiang, Park, Park, Chandra, Wu, Campbel, Lee, Keane, Denniston, Lam, Fung, Chan, Sadda, Loewenstein, Grzybowski, Fong, Wu, Bachmann, Zhang, Yam, Cheung, Pongsachareonnont, Ruamviboonsuk, Raman, Sakamoto, Habash, Girard, Milea, Ang, Tan, Schmetterer, Cheng, Lamoureux, Lin, van Wijngaarden, Wong and Ting.)