Effects of age, gender, and hemisphere on cerebrovascular hemodynamics in children and young adults: Developmental scores and machine learning classifiers.

ABSTRACT: A constant blood supply to the brain is required for mental function. Research with Doppler ultrasonography has important clinical value and burgeoning potential with machine learning applications in studies predicting gestational age and vascular aging. Critically, studies on ultrasound metrics in school-age children are sparse and no machine learning study to date has used color duplex ultrasonography to predict age and classify age-group. The purpose of our study is two-fold: first to document cerebrovascular hemodynamics considering age, gender, and hemisphere in three arteries; and second to construct machine learning models that can predict and classify the age and age-group of a participant using ultrasonography metrics. We record peak systolic, end-diastolic, and time-averaged maxi

SUBMITTER: Arsalidou M 

PROVIDER: S-EPMC8815867 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature