Adnexal torsion diagnosis framework with CT-based adaptive preprocessing and deep neural networks.
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| Title: | Adnexal torsion diagnosis framework with CT-based adaptive preprocessing and deep neural networks. |
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| Authors: | Kim SM; School of Computer Science and Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea., Shin HK; School of Computer Science and Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea., Bae SE; School of Computer Science and Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea., Kim JM; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, 41404, Republic of Korea., Lee YH; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, 41404, Republic of Korea., Chong GO; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, 41404, Republic of Korea., Lee J; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, 41944, Republic of Korea., Park JC; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, 41944, Republic of Korea., Lee HJ; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, 41944, Republic of Korea., Park SY; Department of Radiology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, 41404, Republic of Korea., Lee J; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, 41944, Republic of Korea. gyjhlee@knu.ac.kr., Nam WJ; School of Computer Science and Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea. nwj0612@knu.ac.kr. |
| Source: | Scientific reports [Sci Rep] 2026 May 07. Date of Electronic Publication: 2026 May 07. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 42098354 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Adnexal torsion diagnosis framework with CT-based adaptive preprocessing and deep neural networks. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Kim+SM%22">Kim SM</searchLink>; School of Computer Science and Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Shin+HK%22">Shin HK</searchLink>; School of Computer Science and Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Bae+SE%22">Bae SE</searchLink>; School of Computer Science and Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Kim+JM%22">Kim JM</searchLink>; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, 41404, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Lee+YH%22">Lee YH</searchLink>; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, 41404, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Chong+GO%22">Chong GO</searchLink>; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, 41404, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Lee+J%22">Lee J</searchLink>; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, 41944, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Park+JC%22">Park JC</searchLink>; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, 41944, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Lee+HJ%22">Lee HJ</searchLink>; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, 41944, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Park+SY%22">Park SY</searchLink>; Department of Radiology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, 41404, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Lee+J%22">Lee J</searchLink>; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, 41944, Republic of Korea. gyjhlee@knu.ac.kr.<br /><searchLink fieldCode="AU" term="%22Nam+WJ%22">Nam WJ</searchLink>; School of Computer Science and Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea. nwj0612@knu.ac.kr. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101563288%22">Scientific reports</searchLink> [Sci Rep] 2026 May 07. <i>Date of Electronic Publication: </i>2026 May 07. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Nature+Publishing+Group%22">Nature Publishing Group </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101563288 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2045-2322 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220452322%22">20452322 </searchLink><i>NLM ISO Abbreviation: </i>Sci Rep <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=42098354 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s41598-026-50736-3 Languages: – Code: eng Text: English Titles: – TitleFull: Adnexal torsion diagnosis framework with CT-based adaptive preprocessing and deep neural networks. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kim SM – PersonEntity: Name: NameFull: Shin HK – PersonEntity: Name: NameFull: Bae SE – PersonEntity: Name: NameFull: Kim JM – PersonEntity: Name: NameFull: Lee YH – PersonEntity: Name: NameFull: Chong GO – PersonEntity: Name: NameFull: Lee J – PersonEntity: Name: NameFull: Park JC – PersonEntity: Name: NameFull: Lee HJ – PersonEntity: Name: NameFull: Park SY – PersonEntity: Name: NameFull: Lee J – PersonEntity: Name: NameFull: Nam WJ IsPartOfRelationships: – BibEntity: Dates: – D: 07 M: 05 Text: 2026 May 07 Type: published Y: 2026 Identifiers: – Type: issn-electronic Value: 2045-2322 Titles: – TitleFull: Scientific reports Type: main |
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