Retinal photograph-based deep learning algorithms for myopia and a blockchain platform to facilitate artificial intelligence medical research: a retrospective multicohort study

By 2050, almost 5 billion people globally are projected to have myopia, of whom 20% are likely to have high myopia with clinically significant risk of sight-threatening complications such as myopic macular degeneration. These are diagnoses that typically require specialist assessment or measurement...

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Vydané v:The Lancet Digital Health Ročník 3; číslo 5; s. e317 - e329
Hlavní autori: Tan, Tien-En, Anees, Ayesha, Chen, Cheng, Li, Shaohua, Xu, Xinxing, Li, Zengxiang, Xiao, Zhe, Yang, Yechao, Lei, Xiaofeng, Ang, Marcus, Chia, Audrey, Lee, Shu Yen, Wong, Edmund Yick Mun, Yeo, Ian Yew San, Wong, Yee Ling, Hoang, Quan V, Wang, Ya Xing, Bikbov, Mukharram M, Nangia, Vinay, Jonas, Jost B, Chen, Yen-Po, Wu, Wei-Chi, Ohno-Matsui, Kyoko, Rim, Tyler Hyungtaek, Tham, Yih-Chung, Goh, Rick Siow Mong, Lin, Haotian, Liu, Hanruo, Wang, Ningli, Yu, Weihong, Tan, Donald Tiang Hwee, Schmetterer, Leopold, Cheng, Ching-Yu, Chen, Youxin, Wong, Chee Wai, Cheung, Gemmy Chui Ming, Saw, Seang-Mei, Wong, Tien Yin, Liu, Yong, Ting, Daniel Shu Wei
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England Elsevier Ltd 01.05.2021
Elsevier BV
Elsevier
Predmet:
Algorithms
Area Under Curve
Artificial Intelligence
Biomedical Research
Biomedical Research - instrumentation
Biomedical Research - methods
Blockchain
Cohort Studies
Computer applications to medicine. Medical informatics
Datasets as Topic
Deep Learning
Humans
Informatics
Internal Medicine
Macular Degeneration
Macular Degeneration - diagnosis
Myopia
Myopia - diagnosis
Proof of Concept Study
Public Health
R858-859.7
Reproducibility of Results
Retina
Retina - diagnostic imaging
Retrospective Studies
ROC Curve
ISSN:2589-7500, 2589-7500
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Popis
Shrnutí:By 2050, almost 5 billion people globally are projected to have myopia, of whom 20% are likely to have high myopia with clinically significant risk of sight-threatening complications such as myopic macular degeneration. These are diagnoses that typically require specialist assessment or measurement with multiple unconnected pieces of equipment. Artificial intelligence (AI) approaches might be effective for risk stratification and to identify individuals at highest risk of visual loss. However, unresolved challenges for AI medical studies remain, including paucity of transparency, auditability, and traceability. In this retrospective multicohort study, we developed and tested retinal photograph-based deep learning algorithms for detection of myopic macular degeneration and high myopia, using a total of 226 686 retinal images. First we trained and internally validated the algorithms on datasets from Singapore, and then externally tested them on datasets from China, Taiwan, India, Russia, and the UK. We also compared the performance of the deep learning algorithms against six human experts in the grading of a randomly selected dataset of 400 images from the external datasets. As proof of concept, we used a blockchain-based AI platform to demonstrate the real-world application of secure data transfer, model transfer, and model testing across three sites in Singapore and China. The deep learning algorithms showed robust diagnostic performance with areas under the receiver operating characteristic curves [AUC] of 0·969 (95% CI 0·959–0·977) or higher for myopic macular degeneration and 0·913 (0·906–0·920) or higher for high myopia across the external testing datasets with available data. In the randomly selected dataset, the deep learning algorithms outperformed all six expert graders in detection of each condition (AUC of 0·978 [0·957–0·994] for myopic macular degeneration and 0·973 [0·941–0·995] for high myopia). We also successfully used blockchain technology for data transfer, model transfer, and model testing between sites and across two countries. Deep learning algorithms can be effective tools for risk stratification and screening of myopic macular degeneration and high myopia among the large global population with myopia. The blockchain platform developed here could potentially serve as a trusted platform for performance testing of future AI models in medicine. None.
Bibliografia:ObjectType-Article-1
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ISSN:2589-7500
2589-7500
DOI:10.1016/S2589-7500(21)00055-8