{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T14:25:37Z","timestamp":1793715937001,"version":"4.6.1"},"reference-count":36,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,3,2]],"date-time":"2021-03-02T00:00:00Z","timestamp":1614643200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["MOST 109-2121-M-040-001"],"award-info":[{"award-number":["MOST 109-2121-M-040-001"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Gastroesophageal reflux disease (GERD) is a common disease with high prevalence, and its endoscopic severity can be evaluated using the Los Angeles classification (LA grade). This paper proposes a deep learning model (i.e., GERD-VGGNet) that employs convolutional neural networks for automatic classification and interpretation of routine GERD LA grade. The proposed model employs a data augmentation technique, a two-stage no-freezing fine-tuning policy, and an early stopping criterion. As a result, the proposed model exhibits high generalizability. A dataset of images from 464 patients was used for model training and validation. An additional 32 patients served as a test set to evaluate the accuracy of both the model and our trainees. Experimental results demonstrate that the best model for the development set exhibited an overall accuracy of 99.2% (grade A\u2013B), 100% (grade C\u2013D), and 100% (normal group) using narrow-band image (NBI) endoscopy. On the test set, the proposed model resulted in an accuracy of 87.9%, which was significantly higher than the results of the trainees (75.0% and 65.6%). The proposed GERD-VGGNet model can assist automatic classification of GERD in conventional and NBI environments and thereby increase the accuracy of interpretation of the results by inexperienced endoscopists.<\/jats:p>","DOI":"10.3390\/ijerph18052428","type":"journal-article","created":{"date-parts":[[2021,3,2]],"date-time":"2021-03-02T10:36:37Z","timestamp":1614681397000},"page":"2428","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["A Deep Learning Model for Classification of Endoscopic Gastroesophageal Reflux Disease"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8222-0503","authenticated-orcid":false,"given":"Chi-Chih","family":"Wang","sequence":"first","affiliation":[{"name":"Institute of Medicine, Chung Shan Medical University, Taichung 402, Taiwan"},{"name":"School of Medicine, Chung Shan Medical University, Taichung 402, Taiwan"},{"name":"Division of Gastroenterology and Hepatology, Department of Internal Medicine, Chung Shan Medical University Hospital, Taichung 402, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2449-9769","authenticated-orcid":false,"given":"Yu-Ching","family":"Chiu","sequence":"additional","affiliation":[{"name":"Master Program in Medical Informatics, Chung Shan Medical University, Taichung 402, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0995-2986","authenticated-orcid":false,"given":"Wei-Liang","family":"Chen","sequence":"additional","affiliation":[{"name":"Division of Gastroenterology and Hepatology, Department of Internal Medicine, Chung Shan Medical University Hospital, Taichung 402, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tzu-Wei","family":"Yang","sequence":"additional","affiliation":[{"name":"Institute of Medicine, Chung Shan Medical University, Taichung 402, Taiwan"},{"name":"School of Medicine, Chung Shan Medical University, Taichung 402, Taiwan"},{"name":"Division of Gastroenterology and Hepatology, Department of Internal Medicine, Chung Shan Medical University Hospital, Taichung 402, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming-Chang","family":"Tsai","sequence":"additional","affiliation":[{"name":"Institute of Medicine, Chung Shan Medical University, Taichung 402, Taiwan"},{"name":"School of Medicine, Chung Shan Medical University, Taichung 402, Taiwan"},{"name":"Division of Gastroenterology and Hepatology, Department of Internal Medicine, Chung Shan Medical University Hospital, Taichung 402, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8868-1610","authenticated-orcid":false,"given":"Ming-Hseng","family":"Tseng","sequence":"additional","affiliation":[{"name":"Department of Medical Informatics, Chung Shan Medical University, Taichung 402, Taiwan"},{"name":"Information Technology Office, Chung Shan Medical University Hospital, Taichung 402, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1900","DOI":"10.1111\/j.1572-0241.2006.00630.x","article-title":"The Montreal definition and classification of gastroesophageal reflux disease: A global evidence-based consensus","volume":"101","author":"Vakil","year":"2006","journal-title":"Am. 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