Effectiveness of artificial intelligence-endoscopic ultrasound biliary and pancreatic recognition system: a crossover study
10.3760/cma.j.cn321463-20230130-00570
- VernacularTitle:人工智能超声内镜胆胰识别系统有效性的交叉试验
- Author:
Boru CHEN
1
;
Liwen YAO
;
Lihui ZHANG
;
Zihua LU
;
Huiling WU
;
Honggang YU
Author Information
1. 武汉大学人民医院消化内科 消化系统疾病湖北省重点实验室 湖北省消化疾病微创诊治医学临床研究中心，武汉 430060
- Keywords:
Ultrasonography;
Biliary diseases;
Pancreatic diseases;
Deep learning;
Crossover study
- From:
Chinese Journal of Digestive Endoscopy
2023;40(10):778-783
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the effectiveness of the artificial intelligence-endoscopic ultrasound (AI-EUS) biliary and pancreatic recognition system in assisting the recognition of EUS images.Methods:Subjects who received EUS due to suspicious biliary and pancreatic diseases from December 2019 to August 2020 were prospectively collected from the database of Department of Gastroenterology, Renmin Hospital of Wuhan University. Pancreatic EUS images of 28 subjects were included for recognition of pancreas standard station. EUS images of bile duct of 29 subjects were included for recognition of bile duct standard station. Eight new endoscopists from the Gastroenterology Department of Renmin Hospital of Wuhan University read the 57 EUS videos with and without the assistance of AI-EUS biliary and pancreatic recognition system. Accuracy of endoscopists' identification of biliary and pancreatic standard sites with and without the assistance of AI-EUS was compared.Results:The accuracy of pancreas standard station identification of the new endoscopists increased from 67.2% (903/1 344) to 78.4% (1 054/1 344) with the assistance of AI-EUS. The accuracy of bile duct standard station identification increased from 56.4% (523/928) to 73.8% (685/928).Conclusion:AI-EUS biliary and pancreatic recognition system can improve the accuracy of EUS images recognition of biliary and pancreatic system, which can assist diagnosis in clinical work.
