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. 2022 Jun 10;2(6):562. doi: 10.1038/s43587-022-00245-5

Author Correction: Detecting visually significant cataract using retinal photograph-based deep learning

Yih-Chung Tham 1,2,3,#, Jocelyn Hui Lin Goh 1,#, Ayesha Anees 4,#, Xiaofeng Lei 4,#, Tyler Hyungtaek Rim 1,2, Miao-Li Chee 1, Ya Xing Wang 5, Jost B Jonas 6, Sahil Thakur 1, Zhen Ling Teo 1, Ning Cheung 1,2, Haslina Hamzah 1, Gavin S W Tan 1,2, Rahat Husain 1,2, Charumathi Sabanayagam 1,2, Jie Jin Wang 2, Qingyu Chen 7, Zhiyong Lu 7, Tiarnan D Keenan 8, Emily Y Chew 8, Ava Grace Tan 9,10, Paul Mitchell 9, Rick S M Goh 4, Xinxing Xu 4,#, Yong Liu 1,2,4,#, Tien Yin Wong 1,2,11,#, Ching-Yu Cheng 1,2,11,✉,#
PMCID: PMC10154230  PMID: 37118457

Correction to: Nature Aging 10.1038/s43587-022-00171-6, published online 21 February 2022

This paper was originally published under standard Springer Nature license (© The Author(s), under exclusive licence to Springer Nature America, Inc.). It is now available as an Open Access paper under a Creative Commons Attribution 4.0 International license, © The Author(s). In addition, a new affiliation (Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore) has been added for Yih-Chung Tham, and the Acknowledgements have been amended to include the text “This project is supported by the Agency for Science, Technology and Research (A*STAR) under its RIE2020 Health and Biomedical Sciences (HBMS) Industry Alignment Fund Pre-Positioning (IAF-PP) grant no. H20c6a0031. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of the A*STAR.” The changes have been made to the HTML and PDF versions of the article.


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