Tag: Deep learning

Automated assisted clinical diagnosis of retinopathy of prematurity based on deep learning

Authors:Tong Yan,  Lu Wei,  Xu Yangtao,  Li Ying,  Wang Xiaoling,  Chen Changzheng,  Shen Yin DOI: 10.3760/cma.j.issn.2095-0160.2019.08.011 Published 2019-08-10 Cite as Chin J Exp Ophthalmol, 2019,37(8): 647-651. Abstract                              [View PDF] [Read Full Text] Objective To evaluate the application value of an intelligent fundus assisted diagnosis system for […]

Application of standardized manual labeling on identification of retinopathy of prematurity images in deep learning

Authors:Wang Ji,  Zhang Guihua,  Lin Jianwei,  Ji Jie,  Qiu Kunliang,  Zhang Mingzhi DOI: 10.3760/cma.j.issn.2095-0160.2019.08.013 Published 2019-08-10 Cite as Chin J Exp Ophthalmol, 2019,37(8): 653-657. Abstract                              [View PDF] [Read Full Text] Objective To evaluate the application of the standard manual labeling on identification […]

Validation and application of an artificial intelligence robot assisted diagnosis system for diabetic retinopathy

Authors:Gao Shaohui,  Jin Xuemin,  Zhao Zhaoxia,  Yu Weihong,  Chen Youxin,  Sun Yuhui,  Ding Dayong DOI: 10.3760/cma.j.issn.2095-0160.2019.08.016 Published 2019-08-10 Cite as Chin J Exp Ophthalmol, 2019,37(8): 669-673. Abstract                              [View PDF] [Read Full Text] Objective To evaluate the performance of an artificial intelligence (AI) […]

Establishment and application of diabetic retinopathy intelligent assisted diagnostic technology evaluation system based on fundus photography

Authors:Zheng Bo,  Yang Weihua,  Wu Maonian,  Zhu Shaojun,  Weng Ming,  Zhang Xian,  Zhang Minjun DOI: 10.3760/cma.j.issn.2095-0160.2019.08.017 Published 2019-08-10 Cite as Chin J Exp Ophthalmol, 2019,37(8): 674-679. Abstract                              [View PDF] [Read Full Text] Objective To propose a new evaluation system and evaluate the application value of diabetic […]