… of collaterals using radiomic features and machine learning based on the ASPECTS
scoring terminology with non-contrast computed tomography (NCCT). The method includes …

… of collaterals using radiomic features and machine learning based on the ASPECTS scoring
terminology with non-contrast computed tomography (NCCT). The method includes …

… of collaterals using radiomic features and machine learning based on the ASPECTS
scoring terminology with non-contrast computed tomography (NCCT). The method includes …

… Machine learning (ML) models were constructed according to noncontrast computed tomography
… (NCCT) remains the imaging test of choice for early identification of ischemic stroke (23…

… , readily available non-contrast computed tomography (NCCT… in acute ischemic stroke because
collateral circulation allows … approaches, specifically machine learning and deep learning…

… to construct a machine learning model to predict CE stroke. The … non-contrast computed
tomography (NCCT) and computed … standard for assessing collateral circulation in patients with …

… , collateral circulation status, and National Institutes of Health … features from non-contrast
CT images to assess whether the … Therefore, semi-automatic segmentation and deep learning …

… stroke, it is worth noting that the current models developed for this type of research are based
on anterior circulation ischemic stroke … developed and persistent collateral arterial network …

… Methods: In this retrospective study, a total of 102 consecutive patients who presented with
HMCAS on non-contrast computed tomography (… did not assess the collateral circulation state …

… to evaluate collateral circulation in ischemic stroke patients by … non-contrast computed
tomography (NCCT) and machine … A Radiomics-Based Machine Learning Approach to Assess …