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

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
1 Online-Ressource.
Language
Englisch

Bibliographic citation
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

Creator
Ru, Xiaoshuang
Zhao, Shilong
Chen, Weidao
Wu, Jiangfen
Yu, Ruize
Wang, Dawei
Dong, Mengxing
Wu, Qiong
Peng, Daoyong
Song, Yang
Contributor
SpringerLink (Online service)

DOI
10.1186/s12938-023-01193-w
URN
urn:nbn:de:101:1-2024030321111239446577
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
14.08.2025, 10:54 AM CEST

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Associated

  • 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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