Development of a deep learning-based software for calculating cleansing score in small bowel capsule endoscopy
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Nam, Ji Hyung | - |
dc.contributor.author | Hwang, Youngbae | - |
dc.contributor.author | Oh, Dong Jun | - |
dc.contributor.author | Park, Junseok | - |
dc.contributor.author | Kim, Ki Bae | - |
dc.contributor.author | Jung, Min Kyu | - |
dc.contributor.author | Lim, Yun Jeong | - |
dc.date.accessioned | 2021-09-10T06:24:21Z | - |
dc.date.available | 2021-09-10T06:24:21Z | - |
dc.date.issued | 2021-02-24 | - |
dc.identifier.issn | 2045-2322 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/18982 | - |
dc.description.abstract | A standardized small bowel (SB) cleansing scale is currently not available. The aim of this study was to develop an automated calculation software for SB cleansing score using deep learning. Consecutively performed capsule endoscopy cases were enrolled from three hospitals. A 5-step scoring system based on mucosal visibility was trained for deep learning in the training set. Performance of the trained software was evaluated in the validation set. Average cleansing score (1.0 to 5.0) by deep learning was compared to clinical grading (A to C) reviewed by clinicians. Cleansing scores decreased as clinical grading worsened (scores of 4.1, 3.5, and 2.9 for grades A, B, and C, respectively, P<0.001). Adequate preparation was achieved for 91.7% of validation cases. The average cleansing score was significantly different between adequate and inadequate group (4.0 vs. 2.9, P<0.001). ROC curve analysis revealed that a cut-off value of cleansing score at 3.25 had an AUC of 0.977. Diagnostic yields for small, hard-to-find lesions were associated with high cleansing scores (4.3 vs. 3.8, P<0.001). We developed a novel scoring software which calculates objective, automated cleansing scores for SB preparation. The cut-off value we suggested provides a standard criterion for adequate bowel preparation as a quality indicator. | - |
dc.format.extent | 8 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Nature Publishing Group | - |
dc.title | Development of a deep learning-based software for calculating cleansing score in small bowel capsule endoscopy | - |
dc.type | Article | - |
dc.publisher.location | 영국 | - |
dc.identifier.doi | 10.1038/s41598-021-81686-7 | - |
dc.identifier.scopusid | 2-s2.0-85101495023 | - |
dc.identifier.wosid | 000626806200009 | - |
dc.identifier.bibliographicCitation | Scientific Reports, v.11, no.1, pp 1 - 8 | - |
dc.citation.title | Scientific Reports | - |
dc.citation.volume | 11 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 8 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalWebOfScienceCategory | Multidisciplinary Sciences | - |
dc.subject.keywordPlus | GRADING SYSTEM | - |
dc.subject.keywordPlus | QUALITY | - |
dc.subject.keywordPlus | VALIDATION | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(31538) 22, Soonchunhyang-ro, Asan-si, Chungcheongnam-do, Republic of Korea+82-41-530-1114
COPYRIGHT 2021 by SOONCHUNHYANG UNIVERSITY ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.