Machine Learning for Cerebrovascular Disorders

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

Cerebrovascular disease refers to a group of conditions that affect blood flow and the blood vessels in the brain. It is one of the leading causes of mortality and disability worldwide, imposing a significant socioeconomic burden to society. Research on cerebrovascular diseases has been rapidly progressing leading to improvement in the diagnosis and management of patients nowadays. Machine learning holds many promises for further improving clinical care of these disorders. In this chapter, we will briefly introduce general information regarding cerebrovascular disorders and summarize some of the most promising fields in which machine learning shall be valuable to improve research and patient care. More specifically, we will cover the following cerebrovascular disorders: stroke (both ischemic and hemorrhagic), cerebral microbleeds, cerebral vascular malformations, intracranial aneurysms, and cerebral small vessel disease (white matter hyperintensities, lacunes, perivascular spaces).

Original languageEnglish
Title of host publicationNeuromethods
PublisherHumana Press Inc.
Pages921-961
Number of pages41
DOIs
Publication statusPublished - 2023

Publication series

NameNeuromethods
Volume197
ISSN (Print)0893-2336
ISSN (Electronic)1940-6045

Keywords

  • Cerebral microbleeds
  • Cerebral small vessel disease
  • Cerebral vascular malformations
  • Cerebrovascular disorders
  • Intracranial aneurysms
  • Lacunes
  • Machine learning
  • Perivascular spaces
  • Stroke
  • White matter hyperintensities

ASJC Scopus subject areas

  • General Neuroscience
  • General Biochemistry,Genetics and Molecular Biology
  • General Pharmacology, Toxicology and Pharmaceutics
  • Psychiatry and Mental health

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