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Anran Ran

As seen in: Nature, JAMA (The Journal of the American Medical Association), JAMA: Journal of the American Medical Association
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Articles by Anran Ran

An AI-Based OCT System to Detect Diabetic Macular Edema : A Prospective Validation and Noninferiority Randomized Clinical Trial

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By Shuyi Zhang, Anran Ran, Jiaying Zhou, Anni Ling, Kaiser Sham, Yu Zhang, Ziqi Tang, Truong Nguyen, Trường Nguyễn, Dawei Yang, Hunter Yuen, Victor Chan, Mary Ho, Julia Chan Verified, Claire Chow, Stephanie Cheung, Anthony Lai, Cherie Wong, Vivian Hui, Wilson Yip, Alvin Young, Risa Ozaki, Andrea O. Y. Luk, Juliana Chan, Daniel Wong, Xi Wang, Pheng-Ann Heng, Haotian Lin, Sobha Sivaprasad, Kenneth Li Verified, Carmen Chan, Clement C Tham, Timothy Lai, Simon K. H. Szeto, Carol Cheung, Naiman Lam, Thomas C. H. Lam, Charlene C. L. Yim, Matthew C. W. Lam, Amy H. Y. Yu, Andrew C. Y. Mak, Noel C. Y. Chan, Kit-man Loo, Pangfai Chan, Matthew M. H. Luk, Loretta K. P. Lai, Jasmine Shiu
| JAMA: Journal of the American Medical Association Verified
An AI-Based OCT System to Detect Diabetic Macular Edema: A Prospective Validation and Noninferiority Randomized Clinical Trial Key Points Question Can an artificial intelligence (AI)–based optical coherence tomography (AI-OCT) system to detect diabetic macular edema (DME) improve referral performance of diabetic retinopathy screening?
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A deep learning system for predicting time to progression of diabetic retinopathy - Nature Medicine

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By Ruhan Liu, Xiangning Wang, Zhouyu Guan, Anran Ran, Haoxuan Che, Hao Chen, Xiaodong Sun, Ya Xing Wang, Dinggang Shen, Yih-Chung Tham, Ching-Yu Cheng, Huating Li
| Nature Verified
Abstract Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. The risk of DR progression is highly variable among different individuals, making it difficult to predict risk and personalize screening intervals. We developed and validated a deep learning system (DeepDR Plus) to predict time to DR progression within 5 years solely from fundus images. First, we used 717,308 fundus images from 179,327 participants with diabetes to pretrain the system.
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Assessment of Parafoveal Diabetic Macular Ischemia on Optical Coherence Tomography Angiography Images to Predict Diabetic Retinal Disease Progression and Visual Acuity Deterioration | Diabetic Retinopathy | JAMA Ophthalmology | JAMA Network

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By Dawei Yang, Ziqi Tang, Truong Nguyen, Anran Ran
| JAMA (The Journal of the American Medical Association) Verified
Assessment of Parafoveal Diabetic Macular Ischemia on Optical Coherence Tomography Angiography Images to Predict Diabetic Retinal Disease Progression and Visual Acuity Deterioration Key Points Question Can an automated binary diabetic macular ischemia (DMI) algorithm using optical coherence tomography angiography (OCTA) images predict diabetic retinal disease progression and visual acuity (VA) deterioration?
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