Artificial intelligence-enabled screening for diabetic retinopathy: a real-world, multicenter and prospective study

INTRODUCTION: Early screening for diabetic retinopathy (DR) with an efficient and scalable method is highly needed to reduce blindness, due to the growing epidemic of diabetes. The aim of the study was to validate an artificial intelligence-enabled DR screening and to investigate the prevalence of D...

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Detalles Bibliográficos
Autores principales: Zhang, Yifei, Shi, Juan, Peng, Ying, Zhao, Zhiyun, Zheng, Qidong, Wang, Zilong, Liu, Kun, Jiao, Shengyin, Qiu, Kexin, Zhou, Ziheng, Yan, Li, Zhao, Dong, Jiang, Hongwei, Dai, Yuancheng, Su, Benli, Gu, Pei, Su, Heng, Wan, Qin, Peng, Yongde, Liu, Jianjun, Hu, Ling, Ke, Tingyu, Chen, Lei, Xu, Fengmei, Dong, Qijuan, Terzopoulos, Demetri, Ning, Guang, Xu, Xun, Ding, Xiaowei, Wang, Weiqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Epidemiology/Health services research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7580048/
https://www.ncbi.nlm.nih.gov/pubmed/33087340
http://dx.doi.org/10.1136/bmjdrc-2020-001596

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7580048/
https://www.ncbi.nlm.nih.gov/pubmed/33087340
http://dx.doi.org/10.1136/bmjdrc-2020-001596

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