Novel Estimation of Penumbra Zone Based on Infarct Growth Using Machine Learning Techniques in Acute Ischemic Stroke

Novel Estimation of Penumbra Zone Based on Infarct Growth Using Machine Learning Techniques in Acute Ischemic Stroke

While the penumbra zone is traditionally assessed based on perfusion–diffusion mismatch, it can be assessed based on machine learning (ML) prediction of infarct growth. The purpose of this work was to develop and validate an ML method for the prediction of infarct growth distribution and volume, in...

Full description

Bibliographic Details
Main Authors: Yoon-Chul Kim, Hyung Jun Kim, Jong-Won Chung, In Gyeong Kim, Min Jung Seong, Keon Ha Kim, Pyoung Jeon, Hyo Suk Nam, Woo-Keun Seo, Gyeong-Moon Kim, Oh Young Bang
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Journal of Clinical Medicine
Subjects:
stroke
ischemia
machine learning
cerebral infarction
Online Access:https://www.mdpi.com/2077-0383/9/6/1977

Similar Items

Similar Items