Shao-Wei Li, Li-Hui Zhang, Yue Cai, Xian-Bin Zhou, Xin-Yu Fu, Ya-Qi Song, Shi-Wen Xu, Shen-Ping Tang, Ren-Quan Luo, Qin Huang, Ling-Ling Yan, Sai-Qin He, Yu Zhang, Jun Wang, Shu-Qiong Ge, Bin-Bin Gu, Jin-Bang Peng, Yi Wang, Li-Na Fang, Wei-Dan Wu, Wen-Guang Ye, Min Zhu, Ding-Hai Luo, Xiu-Xiu Jin, Hai-Deng Yang, Jing-Jing Zhou, Zhen-Zhen Wang, Jian-Fen Wu, Qiao-Qiao Qin, Yan-di Lu, Fei Wang, Ya-Hong Chen, Xia Chen, Shan-Jing Xu, Tao-Hsin Tung, Chen-Wen Luo, Li-Ping Ye, Hong-Gang Yu, Xin-Li Mao
Endoscopy is the primary modality for detecting asymptomatic esophageal squamous cell carcinoma (ESCC) and precancerous lesions. Improving detection rate remains challenging. We developed a system based on deep convolutional neural networks (CNNs) for detecting esophageal cancer and precancerous lesions [high-risk esophageal lesions (HrELs)] and validated its efficacy in improving HrEL detection rate in clinical practice (trial registration ChiCTR2100044126 at www.chictr.org.cn). Between April 2021 and March 2022, 3117 patients ≥50 years old were consecutively recruited from Taizhou Hospital, Zhejiang Province, and randomly assigned 1:1 to an experimental group (CNN-assisted endoscopy) or a control group (unassisted endoscopy) based on block randomization...
April 17, 2024: Science Translational Medicine