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Multi-step validation of a deep learning-based system with visual explanations for optical diagnosis of polyps with advanced features.
Zhang, Qing-Wei; Zhang, Zhengjie; Xu, Jianwei; Dai, Zi-Hao; Zhao, Ran; Huang, Jian; Qiu, Hong; Tang, Zhao-Rong; Niu, Bo; Zhang, Xun-Bing; Wang, Peng-Fei; Yang, Mei; Deng, Wan-Yin; Lin, Yan-Sheng; Xiang, Suncheng; Ge, Zhi-Zheng; Qian, Dahong; Li, Xiao-Bo.
Afiliación
  • Zhang QW; Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China.
  • Zhang Z; School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Xu J; School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Dai ZH; Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China.
  • Zhao R; Department of Gastroenterology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China.
  • Huang J; Department of Gastroenterology, Yuyao People's Hospital, Medical School of Ningbo University, Ningbo, Zhejiang Province, China.
  • Qiu H; Department of Gastroenterology and Hepatology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.
  • Tang ZR; Department of Gastroenterology and Hepatology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.
  • Niu B; Department of Digestive Endoscopy Center, Yuncheng First Hospital, Yuncheng, Shanxi Province, China.
  • Zhang XB; Department of Digestive Endoscopy Center, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
  • Wang PF; First Division of Gastroenterology Department, Lanzhou University Second Hospital, Lanzhou, Gansu Province, China.
  • Yang M; Department of Gastroenterology and Hepatology, The Third People's Hospital of Chengdu, Chengdu, Sichuan Province, China.
  • Deng WY; Department of Digestive Endoscopy Center, Fujian Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, China.
  • Lin YS; Department of Medicine, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China.
  • Xiang S; School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Ge ZZ; Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China.
  • Qian D; School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Li XB; Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China.
iScience ; 27(4): 109461, 2024 Apr 19.
Article en En | MEDLINE | ID: mdl-38550997
ABSTRACT
Artificial intelligence (AI) has been found to assist in optical differentiation of hyperplastic and adenomatous colorectal polyps. We investigated whether AI can improve the accuracy of endoscopists' optical diagnosis of polyps with advanced features. We introduced our AI system distinguishing polyps with advanced features with more than 0.870 of accuracy in the internal and external validation datasets. All 19 endoscopists with different levels showed significantly lower diagnostic accuracy (0.410-0.580) than the AI. Prospective randomized controlled study involving 120 endoscopists into optical diagnosis of polyps with advanced features with or without AI demonstration identified that AI improved endoscopists' proportion of polyps with advanced features correctly sent for histological examination (0.960 versus 0.840, p < 0.001), and the proportion of polyps without advanced features resected and discarded (0.490 versus 0.380, p = 0.007). We thus developed an AI technique that significantly increases the accuracy of colorectal polyps with advanced features.
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Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: IScience Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: IScience Año: 2024 Tipo del documento: Article País de afiliación: China