Shin-Ei Kudo, Yuichi Mori, Usama M Abdel-Aal, Masashi Misawa, Hayato Itoh, Masahiro Oda, Kensaku Mori
{"title":"Artificial intelligence and computer-aided diagnosis for colonoscopy: where do we stand now?","authors":"Shin-Ei Kudo, Yuichi Mori, Usama M Abdel-Aal, Masashi Misawa, Hayato Itoh, Masahiro Oda, Kensaku Mori","doi":"10.21037/tgh.2019.12.14","DOIUrl":null,"url":null,"abstract":"<p><p>Computer-aided diagnosis (CAD) for colonoscopy with use of artificial intelligence (AI) is catching increased attention of endoscopists. CAD allows automated detection and pathological prediction, namely optical biopsy, of colorectal polyps during real-time endoscopy, which help endoscopists avoid missing and/or misdiagnosing colorectal lesions. With the increased number of publications in this field and emergence of the AI medical device that have already secured regulatory approval, CAD in colonoscopy is now being implemented into clinical practice. On the other side, drawbacks and weak points of CAD in colonoscopy have not been thoroughly discussed. In this review, we provide an overview of CAD for optical biopsy of colorectal lesions with a particular focus on its clinical applications and limitations.</p>","PeriodicalId":23267,"journal":{"name":"Translational gastroenterology and hepatology","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573374/pdf/tgh-06-2019.12.14.pdf","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational gastroenterology and hepatology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/tgh.2019.12.14","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 4
Abstract
Computer-aided diagnosis (CAD) for colonoscopy with use of artificial intelligence (AI) is catching increased attention of endoscopists. CAD allows automated detection and pathological prediction, namely optical biopsy, of colorectal polyps during real-time endoscopy, which help endoscopists avoid missing and/or misdiagnosing colorectal lesions. With the increased number of publications in this field and emergence of the AI medical device that have already secured regulatory approval, CAD in colonoscopy is now being implemented into clinical practice. On the other side, drawbacks and weak points of CAD in colonoscopy have not been thoroughly discussed. In this review, we provide an overview of CAD for optical biopsy of colorectal lesions with a particular focus on its clinical applications and limitations.
期刊介绍:
Translational Gastroenterology and Hepatology (Transl Gastroenterol Hepatol; TGH; Online ISSN 2415-1289) is an open-access, peer-reviewed online journal that focuses on cutting-edge findings in the field of translational research in gastroenterology and hepatology and provides current and practical information on diagnosis, prevention and clinical investigations of gastrointestinal, pancreas, gallbladder and hepatic diseases. Specific areas of interest include, but not limited to, multimodality therapy, biomarkers, imaging, biology, pathology, and technical advances related to gastrointestinal and hepatic diseases. Contributions pertinent to gastroenterology and hepatology are also included from related fields such as nutrition, surgery, public health, human genetics, basic sciences, education, sociology, and nursing.