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DeepFundus: A flow-cytometry-like image quality classifier for boosting the whole life cycle of medical artificial intelligence

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收录情况： ◇ SCIE

作者：
Liu Lixue[1] ; Wu Xiaohang[1] ; Lin Duoru[1] ; Zhao Lanqin[1] ; Li Mingyuan[1] ; Yun Dongyuan[1] ; Lin Zhenzhe[1] ; Pang Jianyu[1] ; Li Longhui[1] ; Wu Yuxuan[1] ; Lai Weiyi[1] ; Xiao Wei[1] ; Shang Yuanjun[1] ; Feng Weibo[1] ; Tan Xiao[1] ; Li Qiang[2] ; Liu Shenzhen[2] ; Lin Xinxin[2] ; Sun Jiaxin[2] ; Zhao Yiqi[2] ; Yang Ximei[2] ; Ye Qinying[3] ; Zhong Yuesi[4] ; Huang Xi[4] ; He Yuan[5] ; Fu Ziwei[5] ; Xiang Yi[6] ; Zhang Li[6] ; Zhao Mingwei[7] ; Qu Jinfeng[7] ; Xu Fan[8] ; Lu Peng[8] ; Li Jianqiao[9] ; Xu Fabao[9] ; Wei Wenbin[10] ; Dong Li[10] ; Dai Guangzheng[11] ; He Xingru[12] ; Yan Wentao[13] ; Zhu Qiaolin[13] ; Lu Linna[14] ; Zhang Jiaying[14] ; Zhou Wei[15] ; Meng Xiangda[15] ; Li Shiying[16] ; Shen Mei[16] ; Jiang Qin[17] ; Chen Nan[17] ; Zhou Xingtao[18] ; Li Meiyan[18] ; Wang Yan[19] ; Zou Haohan[19] ; Zhong Hua[20] ; Yang Wenyan[20] ; Shou Wulin[21] ; Zhong Xingwu[22] ; Yang Zhenduo[22] ; Ding Lin[23] ; Hu Yongcheng[24] ; Tan Gang[25] ; He Wanji[26] ; Zhao Xin[26] ; Chen Yuzhong[26] ; Liu Yizhi[1] ; Lin Haotian[1,22,27] ;
机构： [1]State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, Guangdong, China [2]Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China [3]Department of Ophthalmology, Second Affiliated Hospital, Guangdong Medical University, Zhanjiang, Guangdong, China [4]Department of Ophthalmology, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China [5]Department of Ophthalmology, The Second Affiliated Hospital of Xi’an Medical University, Xi’an, Shaanxi, China [6]Department of Ophthalmology, Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China [7]Department of Ophthalmology, People’s Hospital of Peking University, Beijing, China [8]Department of Ophthalmology, People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China [9]Department of Ophthalmology, Qilu Hospital, Shandong University, Jinan, Shandong, China [10]Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China [11]He Eye Specialist Hospital, Shenyang, Liaoning, China [12]School of Public Health, He University, Shenyang, Liaoning, China [13]The Eye Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China [14]Department of Ophthalmology, Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China [15]Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, China [16]Department of Ophthalmology, Xiang’an Hospital of Xiamen University, Xiamen, Fujian, China [17]The Affiliated Eye Hospital of Nanjing Medical University, Nanjing, Jiangsu, China [18]Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, China [19]Tianjin Eye Hospital, Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin Eye Institute, Nankai University, Tianjin, China [20]Department of Ophthalmology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China [21]Jiaxing Chaoju Eye Hospital, Jiaxing, Zhejiang, China [22]Hainan Eye Hospital and Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Haikou, Hainan, China [23]Department of Ophthalmology, People’s Hospital of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, China [24]Bayannur Xudong Eye Hospital, Bayannur, Inner Mongolia, China [25]Department of Ophthalmology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China [26]Beijing Airdoc Technology Co., Ltd., Beijing, China [27]Center for Precision Medicine and Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
出处：
DOI： 10.1016/j.xcrm.2022.100912
ISSN：

摘要：
Medical artificial intelligence (AI) has been moving from the research phase to clinical implementation. However, most AI-based models are mainly built using high-quality images preprocessed in the laboratory, which is not representative of real-world settings. This dataset bias proves a major driver of AI system dysfunction. Inspired by the design of flow cytometry, DeepFundus, a deep-learning-based fundus image classifier, is developed to provide automated and multidimensional image sorting to address this data quality gap. DeepFundus achieves areas under the receiver operating characteristic curves (AUCs) over 0.9 in image classification concerning overall quality, clinical quality factors, and structural quality analysis on both the internal test and national validation datasets. Additionally, DeepFundus can be integrated into both model development and clinical application of AI diagnostics to significantly enhance model performance for detecting multiple retinopathies. DeepFundus can be used to construct a data-driven paradigm for improving the entire life cycle of medical AI practice.Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.

基金：
This project was supported by the National Natural Science Foundation of China (NSFC; grant nos. 82171035 and 82201237), the Science and Technology Program of Guangzhou (grant no. 202201020337), Guangzhou Basic and Applied Basic Research Project (grant no. 202201011301), and the Hainan Province Clinical Medical Center.
语种：
外文
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出版当年[2024]版：
无
最新[2023]版：
大类 | 1 区 医学
小类 | 1 区 医学：研究与实验 2 区 细胞生物学
JCR分区：
出版当年[2023]版：
Q1 CELL BIOLOGY Q1 MEDICINE, RESEARCH & EXPERIMENTAL
最新[2023]版：
Q1 CELL BIOLOGY Q1 MEDICINE, RESEARCH & EXPERIMENTAL

影响因子： 最新[2023版] 最新五年平均 出版当年[2023版] 出版当年五年平均 出版前一年[2022版]

第一作者：
第一作者机构： [1]State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, Guangdong, China
共同第一作者：
通讯作者：
通讯机构： [1]State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, Guangdong, China [22]Hainan Eye Hospital and Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Haikou, Hainan, China [27]Center for Precision Medicine and Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
推荐引用方式(GB/T 7714)：
Liu Lixue,Wu Xiaohang,Lin Duoru,et al.DeepFundus: A flow-cytometry-like image quality classifier for boosting the whole life cycle of medical artificial intelligence[J].CELL REPORTS MEDICINE.2023,4(2):100912.doi:10.1016/j.xcrm.2022.100912.
APA：
Liu Lixue,Wu Xiaohang,Lin Duoru,Zhao Lanqin,Li Mingyuan...&Lin Haotian.(2023).DeepFundus: A flow-cytometry-like image quality classifier for boosting the whole life cycle of medical artificial intelligence.CELL REPORTS MEDICINE,4,(2)
MLA：
Liu Lixue,et al."DeepFundus: A flow-cytometry-like image quality classifier for boosting the whole life cycle of medical artificial intelligence".CELL REPORTS MEDICINE 4..2(2023):100912

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