Cargando…
Prediction of Hemorrhagic Complication after Thrombolytic Therapy Based on Multimodal Data from Multiple Centers: An Approach to Machine Learning and System Implementation
Hemorrhagic complication (HC) is the most severe complication of intravenous thrombolysis (IVT) in patients with acute ischemic stroke (AIS). This study aimed to build a machine learning (ML) prediction model and an application system for a personalized analysis of the risk of HC in patients undergo...
Autores principales: | Cui, Shaoguo, Song, Haojie, Ren, Huanhuan, Wang, Xi, Xie, Zheng, Wen, Hao, Li, Yongmei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9782609/ https://www.ncbi.nlm.nih.gov/pubmed/36556272 http://dx.doi.org/10.3390/jpm12122052 |
Ejemplares similares
-
A clinical–radiomics model based on noncontrast computed tomography to predict hemorrhagic transformation after stroke by machine learning: a multicenter study
por: Ren, Huanhuan, et al.
Publicado: (2023) -
Pulmonary alveolar hemorrhage following thrombolytic therapy
por: Narayanan, Santhosh, et al.
Publicado: (2017) -
Post thrombolytic alveolar hemorrhage: a case report
por: Mardenli, Mahmoud, et al.
Publicado: (2023) -
Change of Serum Biomarkers to Post-Thrombolytic Symptomatic Intracranial Hemorrhage in Stroke
por: Cui, Yu, et al.
Publicado: (2022) -
Risk Factors of Neurological Complications in Severe Fever Patients with Thrombolytic Syndrome: A Single-Center Retrospective Study in China
por: Fei, Xiao, et al.
Publicado: (2021)