CT Angiography Radiomics Combining Traditional Risk Factors to Predict Brain Arteriovenous Malformation Rupture: a Machine Learning, Multicenter Study-Reference-Cited by-同舟云学术

CT Angiography Radiomics Combining Traditional Risk Factors to Predict Brain Arteriovenous Malformation Rupture: a Machine Learning, Multicenter Study

Published:2023-06-13 Issue: Volume: Page:
ISSN:1868-4483
Container-title:Translational Stroke Research
language:en
Short-container-title:Transl. Stroke Res.

Author:

Zhang Shaosen,Wang Junjie,Sun Shengjun,Zhang Qian,Zhai Yuanren,Wang Xiaochen,Ge Peicong,Shi Zhiyong,Zhang Dong

Publisher

Springer Science and Business Media LLC

Subject

Cardiology and Cardiovascular Medicine,Neurology (clinical),General Neuroscience

Link

https://link.springer.com/content/pdf/10.1007/s12975-023-01166-0.pdf

Reference37 articles.

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3. Hernesniemi JA, Dashti R, Juvela S, et al. Natural history of brain arteriovenous malformations: a long-term follow-up study of risk of hemorrhage in 238 patients. Neurosurg. 2008;63:823–9. https://doi.org/10.1227/01.NEU.0000330401.82582.5E.

4. Mohr JP, Parides MK, Stapf C, et al. Medical management with or without interventional therapy for unruptured brain arteriovenous malformations (ARUBA): a multicentre, non-blinded, randomised trial. The Lancet. 2014;383:614–21. https://doi.org/10.1016/S0140-6736(13)62302-8.

5. Mohr JP, Overbey JR, Hartmann A, et al. Medical management with interventional therapy versus medical management alone for unruptured brain arteriovenous malformations (ARUBA): final follow-up of a multicentre, non-blinded, randomised controlled trial. Lancet Neurol. 2020;19:573–81. https://doi.org/10.1016/S1474-4422(20)30181-2.

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