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Exploring the challenge of early gastric cancer diagnostic AI system face in multiple centers and its potential solutions

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收录情况： ◇ SCIE

作者：
Dong Zehua[1,2,3] * ; Tao Xiao[1,2,3] * ; Du Hongliu[1,2,3] ; Wang Junxiao[1,2,3] ; Huang Li[1,2,3] ; He Chiyi[4] ; Zhao Zhifeng[5] ; Mao Xinli[6] ; Ai Yaowei[7] ; Zhang Beiping[8] ; Liu Mei[9] ; Xu Hong[10] ; Jiang Zhenyu[11] ; Sun Yunwei[12] ; Li Xiuling[13] ; Liu Zhihong[14] ; Chen Jinzhong[15] ; Song Ying[16] ; Liu Guowei[17] ; Luo Chaijie[1,2,3] ; Li Yanxia[1,2,3] ; Zeng Xiaoquan[1,2,3] ; Liu Jun[1,2,3] ; Zhu Yijie[1,2,3] ; Wu Lianlian[1,2,3] ; Yu Honggang[1,2,3] ;
单位： [1]Renmin Hospital of Wuhan University, Wuhan, China [2]Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China [3]Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China [4]Department of Gastroenterology, Yijishan Hospital of Wannan Medical College, Wuhu 241001, Anhui, People’s Republic of China [5]Department of Digestive Endoscopy, The Fourth Hospital of China Medical University, Shenyang 110032, Liaoning Province, People’s Republic of China [6]Department of Gastroenterology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, Zhejiang, China [7]Department of Gastroenterology, The People’s Hospital of China Three Gorges University, The First People’s Hospital of Yichang, Yichang, China [8]Department of Gastroenterology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China [9]Department of Gastroenterology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China [10]Department of Endoscopy, The First Hospital of Jilin University, Changchun, China [11]Department of Gastroenterology, The Second Affiliated Hospital of Baotou Medical College, Baotou, Inner Mongolia, China [12]Department of Gastroenterology, Ruijin Hospital, Shanghai Jiaotong University, Gubei Branch, Shanghai, People’s Republic of China [13]Department of Gastroenterology, School of Clinical Medicine, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, Henan University, Zhengzhou, Henan, China [14]Department of Gastroenterology, Jilin City People’s Hospital, Jilin, China [15]Endoscopy Center, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, Xiamen, China
出处：
DOI： 10.1007/s00535-023-02025-3
ISSN：

关键词： Artificial intelligence Early gastric cancer Case diversity

摘要：
Artificial intelligence (AI) performed variously among test sets with different diversity due to sample selection bias, which can be stumbling block for AI applications. We previously tested AI named ENDOANGEL, diagnosing early gastric cancer (EGC) on single-center videos in man-machine competition. We aimed to re-test ENDOANGEL on multi-center videos to explore challenges applying AI in multiple centers, then upgrade ENDOANGEL and explore solutions to the challenge.ENDOANGEL was re-tested on multi-center videos retrospectively collected from 12 institutions and compared with performance in previously reported single-center videos. We then upgraded ENDOANGEL to ENDOANGEL-2022 with more training samples and novel algorithms and conducted competition between ENDOANGEL-2022 and endoscopists. ENDOANGEL-2022 was then tested on single-center videos and compared with performance in multi-center videos; the two AI systems were also compared with each other and endoscopists.Forty-six EGCs and 54 non-cancers were included in multi-center video cohort. On diagnosing EGCs, compared with single-center videos, ENDOANGEL showed stable sensitivity (97.83% vs. 100.00%) while sharply decreased specificity (61.11% vs. 82.54%); ENDOANGEL-2022 showed similar tendency while achieving significantly higher specificity (79.63%, p < 0.01) making fewer mistakes on typical lesions than ENDOANGEL. On detecting gastric neoplasms, both AI showed stable sensitivity while sharply decreased specificity. Nevertheless, both AI outperformed endoscopists in the two competitions.Great increase of false positives is a prominent challenge for applying EGC diagnostic AI in multiple centers due to high heterogeneity of negative cases. Optimizing AI by adding samples and using novel algorithms is promising to overcome this challenge.© 2023. Japanese Society of Gastroenterology.

基金：
College-enterprise Deepening Reform Project of Wuhan University (to Honggang Yu). Artificial Intelligence Application Demonstration Scenario Project Wuhan (grant no.2022YYCJ01) (to Honggang Yu). National Natural Science Foundation of China-Youth Science Fund (grant no.82202257) (To Lianlian Wu). Special projects for knowledge innovation of Wuhan (grant no.2022020801020482) (To Lianlian Wu).
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外文
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出版当年[2022]版：
大类 | 1 区 医学
小类 | 2 区 胃肠肝病学
最新[2025]版：
大类 | 1 区 医学
小类 | 2 区 胃肠肝病学
JCR分区：
出版当年[2021]版：
Q2 GASTROENTEROLOGY & HEPATOLOGY
最新[2023]版：
Q1 GASTROENTEROLOGY & HEPATOLOGY

影响因子： 最新[2023版] 最新五年平均 出版当年[2021版] 出版当年五年平均 出版前一年[2020版] 出版后一年[2022版]

第一作者：
第一作者单位： [1]Renmin Hospital of Wuhan University, Wuhan, China [2]Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China [3]Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
共同第一作者：
通讯作者：
通讯机构： [1]Renmin Hospital of Wuhan University, Wuhan, China [2]Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China [3]Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
推荐引用方式(GB/T 7714)：
Dong Zehua,Tao Xiao,Du Hongliu,et al.Exploring the challenge of early gastric cancer diagnostic AI system face in multiple centers and its potential solutions[J].JOURNAL OF GASTROENTEROLOGY.2023,58(10):978-989.doi:10.1007/s00535-023-02025-3.
APA：
Dong Zehua,Tao Xiao,Du Hongliu,Wang Junxiao,Huang Li...&Yu Honggang.(2023).Exploring the challenge of early gastric cancer diagnostic AI system face in multiple centers and its potential solutions.JOURNAL OF GASTROENTEROLOGY,58,(10)
MLA：
Dong Zehua,et al."Exploring the challenge of early gastric cancer diagnostic AI system face in multiple centers and its potential solutions".JOURNAL OF GASTROENTEROLOGY 58..10(2023):978-989

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