AI assisted detection of large vessel occlusion on non-contrast CT: multinational validation and reader study.

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Title: AI assisted detection of large vessel occlusion on non-contrast CT: multinational validation and reader study.
Authors: Sunwoo L; Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea (the Republic of)., Ryu WS; Artificial Intelligence Research Center, JLK, Seoul, Korea (the Republic of)., Buch K; Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA., Conklin J; Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA., Mehan W; Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA., Desalvo MN; Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, USA., Loken E; Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, USA., Rincon S; Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA., Rocha T; Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, USA., Succi M; Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA., Lee M; Artificial Intelligence Research Center, JLK, Seoul, Korea (the Republic of)., Kim D; Artificial Intelligence Research Center, JLK, Seoul, Korea (the Republic of)., Kim NH; Department of Neurology and Cerebrovascular Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea (the Republic of)., Han JH; Department of Neurology, Korea University Guro Hospital, Seoul, Korea (the Republic of)., Lee K; Department of Neurology, Korea University Guro Hospital, Seoul, Korea (the Republic of)., Jeong Y; Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea (the Republic of)., Yun H; Department of Neurology, Korea University Guro Hospital, Seoul, Korea (the Republic of)., Kim G; Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea (the Republic of)., Lee B; Department of Neurology and Cerebrovascular Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea (the Republic of)., Ko Y; Department of Neurology and Cerebrovascular Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea (the Republic of)., Kwon C; Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea (the Republic of)., Yoo RE; Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea (the Republic of)., Gorelick P; Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA., Bae HJ; Department of Neurology and Cerebrovascular Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea (the Republic of)., Kim CK; Department of Neurology, Korea University Guro Hospital, Seoul, Korea (the Republic of) kim.bj.stroke@gmail.com ckkim7@korea.ac.kr., Kim BJ; Department of Neurology and Cerebrovascular Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea (the Republic of) kim.bj.stroke@gmail.com ckkim7@korea.ac.kr.
Source: Journal of neurointerventional surgery [J Neurointerv Surg] 2026 Jun 02. Date of Electronic Publication: 2026 Jun 02.
Publication Type: Journal Article
Journal Info: Publisher: BMJ Publishing Group Country of Publication: England NLM ID: 101517079 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1759-8486 (Electronic) Linking ISSN: 17598478 NLM ISO Abbreviation: J Neurointerv Surg Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1759-8486
DOI:10.1136/jnis-2026-025339