Literature DB >> 33448515

Artificial intelligence in upper GI endoscopy - current status, challenges and future promise.

Honggang Yu1, Rajvinder Singh2, Seon Ho Shin2, Khek Yu Ho3.   

Abstract

White-light endoscopy with biopsy is the current gold standard modality for detecting and diagnosing upper gastrointestinal (GI) pathology. However, missed lesions remain a challenge. To overcome interobserver variability and learning curve issues, artificial intelligence (AI) has recently been introduced to assist endoscopists in the detection and diagnosis of upper GI neoplasia. In contrast to AI in colonoscopy, current AI studies for upper GI endoscopy are smaller pilot studies. Researchers currently lack large volume, well-annotated, high-quality datasets in gastric cancer, dysplasia in Barrett's esophagus and early esophageal squamous cell cancer. This review will look at the latest studies of AI in upper GI endoscopy, discuss some of the challenges facing researchers, and predict what the future may hold in this rapidly changing field.
© 2020 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Entities:  

Keywords:  Endoscopy; Esophagus; Stomach; Upper GI

Mesh:

Year:  2021        PMID: 33448515     DOI: 10.1111/jgh.15354

Source DB:  PubMed          Journal:  J Gastroenterol Hepatol        ISSN: 0815-9319            Impact factor:   4.029


  2 in total

Review 1.  Artificial intelligence in gastroenterology and hepatology: Status and challenges.

Authors:  Jia-Sheng Cao; Zi-Yi Lu; Ming-Yu Chen; Bin Zhang; Sarun Juengpanich; Jia-Hao Hu; Shi-Jie Li; Win Topatana; Xue-Yin Zhou; Xu Feng; Ji-Liang Shen; Yu Liu; Xiu-Jun Cai
Journal:  World J Gastroenterol       Date:  2021-04-28       Impact factor: 5.742

Review 2.  Machine Learning for Future Subtyping of the Tumor Microenvironment of Gastro-Esophageal Adenocarcinomas.

Authors:  Sebastian Klein; Dan G Duda
Journal:  Cancers (Basel)       Date:  2021-09-30       Impact factor: 6.575

  2 in total

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