Gabriela X. Ortiz, Ana Helena Dias Pereira dos Santos Ulbrich, Gabriele Lenhart, Henrique Dias Pereira dos Santos, Karin Hepp Schwambach, Matheus William Becker, C. Blatt
{"title":"Drug-induced liver injury and COVID-19: Use of artificial intelligence and the updated Roussel Uclaf Causality Assessment Method in clinical practice","authors":"Gabriela X. Ortiz, Ana Helena Dias Pereira dos Santos Ulbrich, Gabriele Lenhart, Henrique Dias Pereira dos Santos, Karin Hepp Schwambach, Matheus William Becker, C. Blatt","doi":"10.35712/aig.v4.i2.36","DOIUrl":null,"url":null,"abstract":"The application of artificial intelligence (AI) in gastrointestinal endoscopy has gained significant traction over the last decade. One of the more recent applications of AI in this field includes the detection of dysplasia and cancer in Barrett’s esophagus (BE). AI using deep learning methods has shown promise as an adjunct to the endoscopist in detecting dysplasia and cancer. Apart from visual detection and diagnosis, AI may also aid in reducing the considerable interobserver variability in identifying and distinguishing dysplasia on whole slide images from digitized BE histology slides. This review aims to provide a comprehensive summary of the key studies thus far as well as providing an insight into the future role of AI in Barrett’s esophagus.","PeriodicalId":359415,"journal":{"name":"Artificial Intelligence in Gastroenterology","volume":"155 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence in Gastroenterology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35712/aig.v4.i2.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The application of artificial intelligence (AI) in gastrointestinal endoscopy has gained significant traction over the last decade. One of the more recent applications of AI in this field includes the detection of dysplasia and cancer in Barrett’s esophagus (BE). AI using deep learning methods has shown promise as an adjunct to the endoscopist in detecting dysplasia and cancer. Apart from visual detection and diagnosis, AI may also aid in reducing the considerable interobserver variability in identifying and distinguishing dysplasia on whole slide images from digitized BE histology slides. This review aims to provide a comprehensive summary of the key studies thus far as well as providing an insight into the future role of AI in Barrett’s esophagus.