1. Artificial intelligence in upper GI endoscopy ‐ current status, challenges and future promise
- Author
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Rajvinder Singh, Honggang Yu, Seon Ho Shin, and Khek Yu Ho
- Subjects
Esophageal Neoplasms ,Colonoscopy ,GI NEOPLASIA ,Endoscopy, Gastrointestinal ,Helicobacter Infections ,Barrett Esophagus ,03 medical and health sciences ,0302 clinical medicine ,Artificial Intelligence ,Stomach Neoplasms ,Humans ,Medicine ,Upper gastrointestinal ,Esophagus ,Hepatology ,medicine.diagnostic_test ,business.industry ,Gold standard ,Gastroenterology ,medicine.disease ,Upper GI endoscopy ,Endoscopy ,medicine.anatomical_structure ,Dysplasia ,Gastritis ,030220 oncology & carcinogenesis ,Carcinoma, Squamous Cell ,030211 gastroenterology & hepatology ,Artificial intelligence ,business ,Precancerous Conditions ,Forecasting - 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.
- Published
- 2021
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