Skoltech researchers and their colleagues from HSE University and York University have presented an extensive dataset of indices derived from ultrasonography scans of three major arteries that supply blood to the brain. The sample consists of 821 participants, most of them attending regular public schools, which is particularly valuable as most of the prior studies dealt either with other age groups or with sick children. The team hopes the new data will serve as a useful reference for clinicians and prompt new developmental, social, and other research. For their part, the authors of the study in PLOS ONE have already trained a machine learning model to tell a child’s age based on ultrasonography indices, proving they can be used to make meaningful predictions.
First-of-its-kind child ultrasonography dataset enables a wealth of research
Skoltech researchers and their colleagues from HSE University and York University have presented an extensive dataset of indices derived from ultrasonography scans of three major arteries that supply blood to the brain. The sample consists of 821 participants, most of them attending regular public schools, which is particularly valuable as most of the prior studies dealt either with other age groups or with sick children. The team hopes the new data will serve as a useful reference for clinicians and prompt new developmental, social, and other research. For their part, the authors of the study in PLOS ONE have already trained a machine learning model to tell a child's age based on ultrasonography indices, proving they can be used to make meaningful predictions.