Hang Viet Dao, Binh Phuc Nguyen, Tung Thanh Nguyen, Hoa Ngoc Lam, Trang Thi Huyen Nguyen, Thao Thi Dang, Long Bao Hoang, Hung Quang Le, Long Van Dao
{"title":"人工智能在越南胃肠内镜检查中的应用:述评。","authors":"Hang Viet Dao, Binh Phuc Nguyen, Tung Thanh Nguyen, Hoa Ngoc Lam, Trang Thi Huyen Nguyen, Thao Thi Dang, Long Bao Hoang, Hung Quang Le, Long Van Dao","doi":"10.1177/26317745241306562","DOIUrl":null,"url":null,"abstract":"<p><p>The utilization of artificial intelligence (AI) in gastrointestinal (GI) endoscopy has witnessed significant progress and promising results in recent years worldwide. From 2019 to 2023, the European Society of Gastrointestinal Endoscopy has released multiple guidelines/consensus with recommendations on integrating AI for detecting and classifying lesions in practical endoscopy. In Vietnam, since 2019, several preliminary studies have been conducted to develop AI algorithms for GI endoscopy, focusing on lesion detection. These studies have yielded high accuracy results ranging from 86% to 92%. For upper GI endoscopy, ongoing research directions comprise image quality assessment, detection of anatomical landmarks, simulating image-enhanced endoscopy, and semi-automated tools supporting the delineation of GI lesions on endoscopic images. For lower GI endoscopy, most studies focus on developing AI algorithms for colorectal polyps' detection and classification based on the risk of malignancy. In conclusion, the application of AI in this field represents a promising research direction, presenting challenges and opportunities for real-world implementation within the Vietnamese healthcare context.</p>","PeriodicalId":40947,"journal":{"name":"Therapeutic Advances in Gastrointestinal Endoscopy","volume":"17 ","pages":"26317745241306562"},"PeriodicalIF":3.0000,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11672465/pdf/","citationCount":"0","resultStr":"{\"title\":\"Application of artificial intelligence in gastrointestinal endoscopy in Vietnam: a narrative review.\",\"authors\":\"Hang Viet Dao, Binh Phuc Nguyen, Tung Thanh Nguyen, Hoa Ngoc Lam, Trang Thi Huyen Nguyen, Thao Thi Dang, Long Bao Hoang, Hung Quang Le, Long Van Dao\",\"doi\":\"10.1177/26317745241306562\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The utilization of artificial intelligence (AI) in gastrointestinal (GI) endoscopy has witnessed significant progress and promising results in recent years worldwide. From 2019 to 2023, the European Society of Gastrointestinal Endoscopy has released multiple guidelines/consensus with recommendations on integrating AI for detecting and classifying lesions in practical endoscopy. In Vietnam, since 2019, several preliminary studies have been conducted to develop AI algorithms for GI endoscopy, focusing on lesion detection. These studies have yielded high accuracy results ranging from 86% to 92%. For upper GI endoscopy, ongoing research directions comprise image quality assessment, detection of anatomical landmarks, simulating image-enhanced endoscopy, and semi-automated tools supporting the delineation of GI lesions on endoscopic images. For lower GI endoscopy, most studies focus on developing AI algorithms for colorectal polyps' detection and classification based on the risk of malignancy. In conclusion, the application of AI in this field represents a promising research direction, presenting challenges and opportunities for real-world implementation within the Vietnamese healthcare context.</p>\",\"PeriodicalId\":40947,\"journal\":{\"name\":\"Therapeutic Advances in Gastrointestinal Endoscopy\",\"volume\":\"17 \",\"pages\":\"26317745241306562\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-12-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11672465/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Therapeutic Advances in Gastrointestinal Endoscopy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/26317745241306562\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"GASTROENTEROLOGY & HEPATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Therapeutic Advances in Gastrointestinal Endoscopy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/26317745241306562","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
Application of artificial intelligence in gastrointestinal endoscopy in Vietnam: a narrative review.
The utilization of artificial intelligence (AI) in gastrointestinal (GI) endoscopy has witnessed significant progress and promising results in recent years worldwide. From 2019 to 2023, the European Society of Gastrointestinal Endoscopy has released multiple guidelines/consensus with recommendations on integrating AI for detecting and classifying lesions in practical endoscopy. In Vietnam, since 2019, several preliminary studies have been conducted to develop AI algorithms for GI endoscopy, focusing on lesion detection. These studies have yielded high accuracy results ranging from 86% to 92%. For upper GI endoscopy, ongoing research directions comprise image quality assessment, detection of anatomical landmarks, simulating image-enhanced endoscopy, and semi-automated tools supporting the delineation of GI lesions on endoscopic images. For lower GI endoscopy, most studies focus on developing AI algorithms for colorectal polyps' detection and classification based on the risk of malignancy. In conclusion, the application of AI in this field represents a promising research direction, presenting challenges and opportunities for real-world implementation within the Vietnamese healthcare context.