A weakly supervised deep learning model integrating noncontrasted computed tomography images and clinical factors facilitates haemorrhagic transformation prediction after intravenous thrombolysis in acute ischaemic stroke patients
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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1 Online-Ressource.
- Sprache
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Englisch
- Erschienen in
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A weakly supervised deep learning model integrating noncontrasted computed tomography images and clinical factors facilitates haemorrhagic transformation prediction after intravenous thrombolysis in acute ischaemic stroke patients ; volume:22 ; number:1 ; day:19 ; month:12 ; year:2023 ; pages:1-17 ; date:12.2023
Biomedical engineering online ; 22, Heft 1 (19.12.2023), 1-17, 12.2023
- Urheber
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Ru, Xiaoshuang
Zhao, Shilong
Chen, Weidao
Wu, Jiangfen
Yu, Ruize
Wang, Dawei
Dong, Mengxing
Wu, Qiong
Peng, Daoyong
Song, Yang
- Beteiligte Personen und Organisationen
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SpringerLink (Online service)
- DOI
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10.1186/s12938-023-01193-w
- URN
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urn:nbn:de:101:1-2024030321111239446577
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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14.08.2025, 10:54 MESZ
Datenpartner
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Beteiligte
- Ru, Xiaoshuang
- Zhao, Shilong
- Chen, Weidao
- Wu, Jiangfen
- Yu, Ruize
- Wang, Dawei
- Dong, Mengxing
- Wu, Qiong
- Peng, Daoyong
- Song, Yang
- SpringerLink (Online service)
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