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.
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
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ISSN:2045-2322
DOI:10.1038/s41598-026-50736-3