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 language | English |
|---|---|
| Title of host publication | Neuromethods |
| Publisher | Humana Press Inc. |
| Pages | 921-961 |
| Number of pages | 41 |
| DOIs | |
| Publication status | Published - 2023 |
Publication series
| Name | Neuromethods |
|---|---|
| Volume | 197 |
| ISSN (Print) | 0893-2336 |
| ISSN (Electronic) | 1940-6045 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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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