Cardiovascular/stroke risk prevention: A new machine learning framework integrating carotid ultrasound image-based phenotypes and its harmonics with conventional risk factors

MOTIVATION: Machine learning (ML)-based stroke risk stratification systems have typically focused on conventional risk factors (CRF) (AtheroRisk-conventional). Besides CRF, carotid ultrasound image phenotypes (CUSIP) have shown to be powerful phenotypes risk stratification. This is the first ML stud...

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Detalles Bibliográficos
Autores principales: Jamthikar, Ankush, Gupta, Deep, Khanna, Narendra N., Saba, Luca, Laird, John R., Suri, Jasjit S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7474133/
https://www.ncbi.nlm.nih.gov/pubmed/32861380
http://dx.doi.org/10.1016/j.ihj.2020.06.004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7474133/
https://www.ncbi.nlm.nih.gov/pubmed/32861380
http://dx.doi.org/10.1016/j.ihj.2020.06.004

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