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Cited 10 time in webofscience Cited 11 time in scopus
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A Current and Newly Proposed Artificial Intelligence Algorithm for Reading Small Bowel Capsule Endoscopy

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dc.contributor.authorOh, Dong Jun-
dc.contributor.authorHwang, Youngbae-
dc.contributor.authorLim, Yun Jeong-
dc.date.accessioned2023-04-27T17:40:18Z-
dc.date.available2023-04-27T17:40:18Z-
dc.date.issued2021-07-
dc.identifier.issn2075-4418-
dc.identifier.issn2075-4418-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/4785-
dc.description.abstractSmall bowel capsule endoscopy (SBCE) is one of the most useful methods for diagnosing small bowel mucosal lesions. However, it takes a long time to interpret the capsule images. To solve this problem, artificial intelligence (AI) algorithms for SBCE readings are being actively studied. In this article, we analyzed several studies that applied AI algorithms to SBCE readings, such as automatic lesion detection, automatic classification of bowel cleanliness, and automatic compartmentalization of small bowels. In addition to automatic lesion detection using AI algorithms, a new direction of AI algorithms related to shorter reading times and improved lesion detection accuracy should be considered. Therefore, it is necessary to develop an integrated AI algorithm composed of algorithms with various functions in order to be used in clinical practice.-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI-
dc.titleA Current and Newly Proposed Artificial Intelligence Algorithm for Reading Small Bowel Capsule Endoscopy-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/diagnostics11071183-
dc.identifier.scopusid2-s2.0-85109844953-
dc.identifier.wosid000676311500001-
dc.identifier.bibliographicCitationDIAGNOSTICS, v.11, no.7-
dc.citation.titleDIAGNOSTICS-
dc.citation.volume11-
dc.citation.number7-
dc.type.docTypeReview-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaGeneral & Internal Medicine-
dc.relation.journalWebOfScienceCategoryMedicine, General & Internal-
dc.subject.keywordPlusDEVICE-ASSISTED ENTEROSCOPY-
dc.subject.keywordPlusDISORDERS EUROPEAN-SOCIETY-
dc.subject.keywordPlusAUTOMATIC DETECTION-
dc.subject.keywordPlusIMAGES-
dc.subject.keywordPlusSOFTWARE-
dc.subject.keywordPlusLESIONS-
dc.subject.keywordPlusPERFORMANCE-
dc.subject.keywordPlusLIMITATIONS-
dc.subject.keywordPlusDIAGNOSIS-
dc.subject.keywordPlusQUALITY-
dc.subject.keywordAuthorartificial intelligence-
dc.subject.keywordAuthorautomatic detection-
dc.subject.keywordAuthorcapsule endoscopy-
dc.subject.keywordAuthorreading software-
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