{"title":"Artificial intelligence for colorectal polyp detection: are we ready for prime time?","authors":"O. Ahmad, L. Lovat","doi":"10.21037/jmai.2019.09.02","DOIUrl":null,"url":null,"abstract":"Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide. Colonoscopy is protective against CRC through the detection and removal of neoplastic polyps. Unfortunately, the procedure is highly operator dependent with significant miss rates for polyps. Artificial intelligence (AI) and computer-aided detection software offers a promising solution by providing real-time assistance to highlight lesions that may otherwise be overlooked. Rapid advances have occurred in the field with recent prospective clinical trials demonstrating an improved adenoma detection rate (ADR) with AI assistance. Deployment in routine clinical practice is possible in the near future although further robust clinical trials are necessary and important practical challenges relating to real-world implementation must be addressed.","PeriodicalId":73815,"journal":{"name":"Journal of medical artificial intelligence","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.21037/jmai.2019.09.02","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of medical artificial intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21037/jmai.2019.09.02","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide. Colonoscopy is protective against CRC through the detection and removal of neoplastic polyps. Unfortunately, the procedure is highly operator dependent with significant miss rates for polyps. Artificial intelligence (AI) and computer-aided detection software offers a promising solution by providing real-time assistance to highlight lesions that may otherwise be overlooked. Rapid advances have occurred in the field with recent prospective clinical trials demonstrating an improved adenoma detection rate (ADR) with AI assistance. Deployment in routine clinical practice is possible in the near future although further robust clinical trials are necessary and important practical challenges relating to real-world implementation must be addressed.