Using a Machine Learning Approach to Predict Outcomes after Radiosurgery for Cerebral Arteriovenous Malformations
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Title
Using a Machine Learning Approach to Predict Outcomes after Radiosurgery for Cerebral Arteriovenous Malformations
Authors
Keywords
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Journal
Scientific Reports
Volume 6, Issue 1, Pages -
Publisher
Springer Nature
Online
2016-02-09
DOI
10.1038/srep21161
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Note: Only part of the references are listed.- Validation of the Supplemented Spetzler-Martin Grading System for Brain Arteriovenous Malformations in a Multicenter Cohort of 1009 Surgical Patients
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- Embolization-induced angiogenesis in cerebral arteriovenous malformations
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- (2013) Dale Ding et al. NEUROSURGERY
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- Hemorrhage Risk of Cerebral Arteriovenous Malformations Before and During the Latency Period After Gamma Knife Radiosurgery
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- A Modified Radiosurgery-Based Arteriovenous Malformation Grading Scale and Its Correlation With Outcomes
- (2010) Rodney E. Wegner et al. INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS
- A prospective, multicenter, randomized trial of the Onyx liquid embolic system and N-butyl cyanoacrylate embolization of cerebral arteriovenous malformations
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- Principal Risk of Peritumoral Edema After Stereotactic Radiosurgery for Intracranial Meningioma Is Tumor-Brain Contact Interface Area
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- A Supplementary Grading Scale for Selecting Patients With Brain Arteriovenous Malformations for Surgery
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- (2009) Bruce E. Pollock et al. NEUROSURGERY
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