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Daniel S. Kermany
Researcher at Guangzhou Medical University
Publications - 8
Citations - 3608
Daniel S. Kermany is an academic researcher from Guangzhou Medical University. The author has contributed to research in topics: Optical coherence tomography & Medicine. The author has an hindex of 5, co-authored 5 publications receiving 2067 citations. Previous affiliations of Daniel S. Kermany include University of California, San Diego.
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Journal ArticleDOI
Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning
Daniel S. Kermany,Daniel S. Kermany,Michael H. Goldbaum,Wenjia Cai,Carolina C. S. Valentim,Huiying Liang,Sally L. Baxter,Alex McKeown,Ge Yang,Xiaokang Wu,Fangbing Yan,Justin Dong,Made K. Prasadha,Jacqueline Pei,Jacqueline Pei,Magdalene Yin Lin Ting,Jie Zhu,Christina Li,Sierra Hewett,Sierra Hewett,Jason Dong,Ian Ziyar,Alexander Shi,Runze Zhang,Lianghong Zheng,Rui Hou,William Shi,Xin Fu,Xin Fu,Yaou Duan,Viet Anh Nguyen Huu,Viet Anh Nguyen Huu,Cindy Wen,Edward Zhang,Edward Zhang,Charlotte Zhang,Charlotte Zhang,Oulan Li,Oulan Li,Xiaobo Wang,Michael A Singer,Xiaodong Sun,Jie Xu,Ali Tafreshi,M. Anthony Lewis,Huimin Xia,Kang Zhang +46 more
TL;DR: A diagnostic tool based on a deep-learning framework for the screening of patients with common treatable blinding retinal diseases, which demonstrates performance comparable to that of human experts in classifying age-related macular degeneration and diabetic macular edema.
Journal ArticleDOI
Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence
Huiying Liang,Brian Tsui,Hao Ni,Carolina C. S. Valentim,Sally L. Baxter,Guangjian Liu,Wenjia Cai,Daniel S. Kermany,Daniel S. Kermany,Xin Sun,Jiancong Chen,Liya He,Jie Zhu,Pin Tian,Hua Shao,Lianghong Zheng,Rui Hou,Sierra Hewett,Sierra Hewett,Gen Li,Gen Li,Ping Liang,Xuan Zang,Zhiqi Zhang,Liyan Pan,Huimin Cai,Rujuan Ling,Shuhua Li,Yongwang Cui,Shusheng Tang,Hong Ye,Xiaoyan Huang,Waner He,Wenqing Liang,Qing Zhang,Jianmin Jiang,Wei Yu,Jianqun Gao,Wanxing Ou,Yingmin Deng,Qiaozhen Hou,Bei Wang,Cuichan Yao,Yan Liang,Shu Zhang,Yaou Duan,Runze Zhang,Sarah Gibson,Charlotte Zhang,Oulan Li,Edward Zhang,Gabriel Karin,Nathan Nguyen,Xiaokang Wu,Xiaokang Wu,Cindy Wen,Jie Xu,Wenqin Xu,Bochu Wang,Winston Wang,Jing Li,Jing Li,Bianca Pizzato,Caroline Bao,Daoman Xiang,Wanting He,Wanting He,Suiqin He,Yugui Zhou,Yugui Zhou,Weldon W Haw,Weldon W Haw,Michael H. Goldbaum,Adriana H. Tremoulet,Chun-Nan Hsu,Hannah Carter,Long Zhu,Kang Zhang,Kang Zhang,Kang Zhang,Huimin Xia +80 more
TL;DR: This study shows that MLCs can query EHRs in a manner similar to the hypothetico-deductive reasoning used by physicians and unearth associations that previous statistical methods have not found, and provides a proof of concept for implementing an AI-based system to aid physicians in tackling large amounts of data, augmenting diagnostic evaluations, and to provide clinical decision support in cases of diagnostic uncertainty or complexity.