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A neuroendocrine tumor lesion detection algorithm based on the YOLOv7 model is developed and assessed for its ability to identify rNETs from white-light endoscopic images. In total, 137,748 images are analyzed and the model’s performance is compared with endoscopists across experience levels. The algorithm demonstrates strong diagnostic accuracy and high specificity, supporting effective rNET lesion detection.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/artificial-intelligence-assisted-diagnosis-of-rectal-neuroendocrine-tumors-during-white-light-endoscopy-original-article/406460/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/artificial-intelligence-assisted-diagnosis-of-rectal-neuroendocrine-tumors-during-white-light-endoscopy-original-article/406460.png","ImageObject",300,407,{"name":92,"@type":93},"Pentious","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-09-28",true,{"@type":102,"interactionType":103,"userInteractionCount":39},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why are rectal neuroendocrine tumors often misdiagnosed during white-light endoscopy?","Question",{"text":112,"@type":113},"Their incidence is much lower than colorectal polyps and their macroscopic features resemble hyperplastic polyps, leading to frequent misdiagnosis and polyp resection.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What algorithm and data were used to detect rNET lesions?",{"text":117,"@type":113},"The study established a lesion detection algorithm based on the YOLOv7 model and used 137,748 white-light endoscopic images, including labeled rNET and other lesion and normal mucosa images.",{"name":119,"@type":110,"acceptedAnswer":120},"How did the YOLOv7-based model perform compared with endoscopists?",{"text":121,"@type":113},"The model achieved 97.8% accuracy with 99.7% specificity and showed effective rNET lesion detection, reported as better than that of most endoscopists.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},406460,1790659775,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":39,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},1374404730887,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","| W | J | G | World Journal of\u003Cbr>Gastroenterology |\n| --- | --- | --- | --- |\n\nSubmit a Manuscript: [https://www.f6publishing.com](https://www.f6publishing.com) World J Gastroenterol 2025 December 28; 31(48): 112683  \nDOI: 10.3748/wjg.v31.i48.112683 ISSN 1007-9327 (print) ISSN 2219-2840 (online)  \nORIGINAL ARTICLE  \nRetrospective Cohort Study  \nArtificial intelligence-assisted diagnosis of rectal neuroendocrine tumors during white-light endoscopy  \nKe Liu, Zhen-Yu Wang, Li-Zhi Yi, Feng Li, Shun-Hui He, Xi-Gang Zhang, Chun-Xiao Lai, Zhi-Jian Li, Lin Qiu, Rui-Ya Zhang, Wen Wu, Yu Lin, Hui Yang, Gui-Ming Liu, Quan-Sheng Guan, Zhi-Fang Zhao, Li-Ming Cheng, Jie Dai, Yang Bai, Fang Xie, Meng-Nan Zhang, Su-Zuan Chen, Xian-Fei Zhong  \nSpecialty type: Gastroenterology and hepatology  \nProvenance and peer review:  \nUnsolicited article; Externally peer reviewed.  \nPeer-review model: Single blind  \nPeer-review report’s classification Scientific Quality: Grade A, Grade A, Grade B, Grade B  \nNovelty: Grade A, Grade A, Grade B, Grade C  \nCreativity or Innovation: Grade A, Grade B, Grade B, Grade C Scientific Significance: Grade B, Grade B, Grade B, Grade B  \nP-Reviewer: Kehagias D, MD, PhD, Greece; Zhu HC, Professor, China  \nReceived: August 4, 2025  \nRevised: September 17, 2025  \nAccepted: November 12, 2025  \nPublished online: December 28, 2025  \nProcessing time: 146 Days and 10.8 Hours  \nKe Liu, Li-Zhi Yi, Xian-Fei Zhong, Department of Gastroenterology, The People’s Hospital of Leshan, Southwest Medical University, Leshan 614000, Sichuan Province, China  \nZhen-Yu Wang, Su-Zuan Chen, Department of Digestive Endoscope, The First Affiliated Hospital of Shantou University Medical College, Shantou 515000, Guangdong Province, China  \nFeng Li, Lin Qiu, Yang Bai, Fang Xie, Meng-Nan Zhang, Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, Guangdong Province, China  \nShun-Hui He, Zhi-Jian Li, Department of Gastroenterology, The Eighth Affiliated Hospital of Southern Medical University, Guangzhou 510515, Guangdong Province, China  \nXi-Gang Zhang, Department of Gastroenterology, Shenzhen Second People’s Hospital, Shenzhen 518020, Guangdong Province, China  \nChun-Xiao Lai, Gastrointestinal Cancer Center, Baiyun Branch, Nanfang Hospital, Southern Medical University, Guangzhou 510515, Guangdong Province, China  \nRui-Ya Zhang, Department of Gastroenterology, The Fifth Clinical Medical College of Shanxi Medical University, Taiyuan 030012, Shanxi Province, China  \nWen Wu, Department of Gastroenterology, Shanxi Academy of Traditional Chinese Medicine, Taiyuan 030024, Shanxi Province, China  \nYu Lin, Department of Gastroenterology, Southern Medical University Hospital of Integrated Traditional Chinese and Western Medicine, Southern Medical University, Guangzhou 510515, Guangdong Province, China  \nHui Yang, Department of Spleen and Stomach, Rizhao Hospital of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Rizhao 276800, Shandong Province, China  \nGui-Ming Liu, Quan-Sheng Guan, Department of Gastroenterology, Shayang Hospital of Traditional Chinese Medicine, Jingmen 448200, Hubei Province, China  \nZhi-Fang Zhao, Department of Gastroenterology, National Institution of Drug Clinical Trial, Guizhou Provincial People’s Hospital, Medical College of Guizhou University, Guiyang  \n WJG  [https://www.wjgnet.com](https://www.wjgnet.com) 1 December 28, 2025  Volume 31  Issue 48   \nLiu K et al. AI-assisted diagnosis of rNETs  \n550000, Guizhou Province, China  \nLi-Ming Cheng, Department of Internal Medicine, Taihe People’s Hospital Baiyun District, Guangzhou 510515, Guangdong Province, China  \nJie Dai, Suzhou Wellomen Information Technology Co. Ltd., Suzhou 215000, Jiangsu Province, China  \nCorresponding author: Xian-Fei Zhong, Department of Gastroenterology, The People’s Hospital of Leshan, Southwest Medical University, No. 238 White Tower Road, Leshan 614000, Sichuan Province, [China.](Chi","cbCaigPD6saBlz2V","https://ap.wps.com/l/cbCaigPD6saBlz2V","pdf",10789740,13,"English","# Abstract\n## Background\n## Aim\n## Methods\n## Results\n## Conclusion\n## Key Words","[{\"question\":\"Why are rectal neuroendocrine tumors often misdiagnosed during white-light endoscopy?\",\"answer\":\"Their incidence is much lower than colorectal polyps and their macroscopic features resemble hyperplastic polyps, leading to frequent misdiagnosis and polyp resection.\"},{\"question\":\"What algorithm and data were used to detect rNET lesions?\",\"answer\":\"The study established a lesion detection algorithm based on the YOLOv7 model and used 137,748 white-light endoscopic images, including labeled rNET and other lesion and normal mucosa images.\"},{\"question\":\"How did the YOLOv7-based model perform compared with endoscopists?\",\"answer\":\"The model achieved 97.8% accuracy with 99.7% specificity and showed effective rNET lesion detection, reported as better than that of most endoscopists.\"}]","Artificial intelligence-assisted diagnosis of rectal neuroendocrine tumors during white-light endoscopy - Original Article | PDF",1790565816,33]