Crossmark

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

Crossref DOI link: https://doi.org/10.1186/s12938-023-01193-w

Published Online: 2023-12-19

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Ru, Xiaoshuang

Zhao, Shilong

Chen, Weidao

Wu, Jiangfen

Yu, Ruize

Wang, Dawei

Dong, Mengxing

Wu, Qiong

Peng, Daoyong

Song, Yang
License Information

Text and Data Mining valid from 2023-12-19

Version of Record valid from 2023-12-19
More Information

Article History

Received: 28 January 2023

Accepted: 9 December 2023

First Online: 19 December 2023

Declarations

:

: This study protocol was reviewed and approved by the Ethics Committee of Central Hospital of Dalian University of Technology. The requirement for informed consent was waived by the ethical committee owing to the retrospective study design and the use of anonymized brain NCCT images.

: Not applicable.

: The authors declare that they have no competing interests.

Document is current

Any future updates will be listed below