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Lesion-Based Convolutional Neural Network in Diagnosis of Early Gastric Cancer

DC Field Value Language
dc.contributor.author김지현-
dc.contributor.author윤홍진-
dc.date.accessioned2020-06-17T00:43:03Z-
dc.date.available2020-06-17T00:43:03Z-
dc.date.issued2020-03-
dc.identifier.issn2234-2400-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/176094-
dc.description.abstractDiagnosis and evaluation of early gastric cancer (EGC) using endoscopic images is significantly important; however, it has some limitations. In several studies, the application of convolutional neural network (CNN) greatly enhanced the effectiveness of endoscopy. To maximize clinical usefulness, it is important to determine the optimal method of applying CNN for each organ and disease. Lesion�-based CNN is a type of deep learning model designed to learn the entire lesion from endoscopic images. This review describes the application of lesion-based CNN technology in diagnosis of EGC.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherKorean Society of Gastrointestinal Endoscopy-
dc.relation.isPartOfCLINICAL ENDOSCOPY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleLesion-Based Convolutional Neural Network in Diagnosis of Early Gastric Cancer-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Internal Medicine (내과학교실)-
dc.contributor.googleauthorHong Jin Yoon-
dc.contributor.googleauthorJie-Hyun Kim-
dc.identifier.doi10.5946/ce.2020.046-
dc.contributor.localIdA00996-
dc.contributor.localIdA04618-
dc.relation.journalcodeJ00572-
dc.identifier.eissn2234-2443-
dc.identifier.pmid32252505-
dc.subject.keywordArtificial intelligence-
dc.subject.keywordConvolutional neural networks-
dc.subject.keywordEarly gastric cancer-
dc.subject.keywordEndoscopy-
dc.subject.keywordInvasion depth-
dc.contributor.alternativeNameKim, Jie-Hyun-
dc.contributor.affiliatedAuthor김지현-
dc.contributor.affiliatedAuthor윤홍진-
dc.citation.volume53-
dc.citation.number2-
dc.citation.startPage127-
dc.citation.endPage131-
dc.identifier.bibliographicCitationCLINICAL ENDOSCOPY, Vol.53(2) : 127-131, 2020-03-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers

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