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

In Cell reports. Medicine

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.

Liu Lixue, Wu Xiaohang, Lin Duoru, Zhao Lanqin, Li Mingyuan, Yun Dongyuan, Lin Zhenzhe, Pang Jianyu, Li Longhui, Wu Yuxuan, Lai Weiyi, Xiao Wei, Shang Yuanjun, Feng Weibo, Tan Xiao, Li Qiang, Liu Shenzhen, Lin Xinxin, Sun Jiaxin, Zhao Yiqi, Yang Ximei, Ye Qinying, Zhong Yuesi, Huang Xi, He Yuan, Fu Ziwei, Xiang Yi, Zhang Li, Zhao Mingwei, Qu Jinfeng, Xu Fan, Lu Peng, Li Jianqiao, Xu Fabao, Wei Wenbin, Dong Li, Dai Guangzheng, He Xingru, Yan Wentao, Zhu Qiaolin, Lu Linna, Zhang Jiaying, Zhou Wei, Meng Xiangda, Li Shiying, Shen Mei, Jiang Qin, Chen Nan, Zhou Xingtao, Li Meiyan, Wang Yan, Zou Haohan, Zhong Hua, Yang Wenyan, Shou Wulin, Zhong Xingwu, Yang Zhenduo, Ding Lin, Hu Yongcheng, Tan Gang, He Wanji, Zhao Xin, Chen Yuzhong, Liu Yizhi, Lin Haotian

2023-Jan-10

artificial intelligence, image quality, retinal diseases