Development and application of an artificial intelligence-assisted endoscopy system for diagnosis of Helicobacter pylori infection: a multicenter randomized controlled study

Development and application of an artificial intelligence-assisted endoscopy system for diagnosis of Helicobacter pylori infection: a multicenter randomized controlled study

Abstract Background The early diagnosis and treatment of Heliobacter pylori (H.pylori) gastrointestinal infection provide significant benefits to patients. We constructed a convolutional neural network (CNN) model based on an endoscopic system to diagnose H. pylori infection, and then examined the p...

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Bibliographic Details
Main Authors: Pei-Ying Zou, Jian-Ru Zhu, Zhe Zhao, Hao Mei, Jing-Tao Zhao, Wen-Jing Sun, Guo-Hua Wang, Dong-Feng Chen, Li-Lin Fan, Chun-Hui Lan
Format: Article
Language:English
Published: BMC 2024-09-01
Series:BMC Gastroenterology
Subjects:
Helicobacter pylori
Endoscopy
Artificial intelligence
Convolutional neural network
Online Access:https://doi.org/10.1186/s12876-024-03389-3

Internet

https://doi.org/10.1186/s12876-024-03389-3

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