Using deep learning and explainable artificial intelligence to assess the severity of gastroesophageal reflux disease according to the Los Angeles Classification System-Reference-Cited by-同舟云学术

Using deep learning and explainable artificial intelligence to assess the severity of gastroesophageal reflux disease according to the Los Angeles Classification System

Published:2023-01-09 Issue:6 Volume:58 Page:596-604
ISSN:0036-5521
Container-title:Scandinavian Journal of Gastroenterology
language:en
Short-container-title:Scandinavian Journal of Gastroenterology

Author:

Ge Zhenyang¹²,Wang Bowen³,Chang Jiuyang⁴⁵,Yu Zequn⁶,Zhou Zhenyuan⁷,Zhang Jing²,Duan Zhijun¹

Affiliation:

1. Department of Gastroenterology, The First Affiliated Hospital of Dalian Medical University, Dalian, China

2. Department of Digestive Endoscopy, Dalian Municipal Central Hospital, Dalian, China

3. Science and Technology, Graduate School of Information, Osaka University, Yamadaoka, Osaka, Japan

4. Department of Cardiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China

5. Department of Cardiovascular Medicine, Graduate School of Medicine, Osaka University, Yamadaoka, Osaka, Japan

6. Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China

7. Information Management Department, Dalian Municipal Central Hospital, Dalian, China

Publisher

Informa UK Limited

Subject

Gastroenterology

Link

https://www.tandfonline.com/doi/pdf/10.1080/00365521.2022.2163185

Reference48 articles.

1. Modern diagnosis of GERD: the Lyon Consensus

2. The role of endoscopy in the management of GERD

3. The Los Angeles and Savary-Miller systems for grading esophagitis: utilization and correlation with histology

4. The role of endoscopy in the management of gastroesophageal reflux disease

5. Relationship between esophageal motility and severity of gastroesophageal reflux disease according to the Los Angeles classification

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