Machine learning-based predictive model for the development of thrombolysis resistance in patients with acute ischemic stroke-Reference-Cited by-同舟云学术

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Machine learning-based predictive model for the development of thrombolysis resistance in patients with acute ischemic stroke

Published:2024-08-26 Issue:1 Volume:24 Page:
ISSN:1471-2377
Container-title:BMC Neurology
language:en
Short-container-title:BMC Neurol

Author:

Wang Xiaorui,Luo Song,Cui Xue,Qu Hongdang,Zhao Yujie,Liao Qirong

Funder

Clinical Medicine Research and Translational Project of Anhui Province

the Bengbu Science and Technology Innovation Guidance Category

the University Natural Science Research Project of Anhui Province

Anhui Province Jianghuai Famous Doctor Cultivation Project

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1186/s12883-024-03781-2.pdf

Reference39 articles.

1. Saini V, Guada L, Yavagal DR. Global Epidemiology of Stroke and Access to acute ischemic stroke interventions. Neurology. 2021;97(20 Suppl 2):S6–16.

2. Leng T, Xiong ZG. Treatment for ischemic stroke: from thrombolysis to thrombectomy and remaining challenges. Brain Circ. 2019;5(1):8–11.

3. Tu WJ, Wang LD. Special Writing Group of China Stroke Surveillance Report. China stroke surveillance report 2021. Mil Med Res. 2023;10(1):33.

4. Herpich F, Rincon F. Management of Acute ischemic stroke. Crit Care Med. 2020;48(11):1654–63.

5. Tseng YJ, Hu RF, Lee ST, et al. Risk factors Associated with outcomes of recombinant tissue plasminogen activator therapy in patients with Acute ischemic stroke. Int J Environ Res Public Health. 2020;17(2):618.

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