Intervening Nidal Brain Parenchyma and Risk of Radiation-Induced Changes After Radiosurgery for Brain Arteriovenous Malformation: A Study Using an Unsupervised Machine Learning Algorithm. [electronic resource]
Producer: 20191209Description: e132-e138 p. digitalISSN:- 1878-8769
- Adolescent
- Adult
- Aged
- Algorithms
- Brain -- radiation effects
- Child
- Female
- Humans
- Intracranial Arteriovenous Malformations -- radiotherapy
- Male
- Middle Aged
- Parenchymal Tissue -- radiation effects
- Prospective Studies
- Radiation Injuries -- etiology
- Radiosurgery -- adverse effects
- Risk Factors
- Unsupervised Machine Learning
- Young Adult
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Publication Type: Journal Article
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