Topic: supervised machine learning

Brain development is fastest at the end of pregnancy and soon after birth. Neonatal brain function can thus offer fundamental insights into brain organization, but many existing functional neural measures are poor predictors of chronological age. Analysis of signal complexity (e.g. entropy) has been demonstrated to be powerful methodology in various fields of research, including life sciences. In this cross-validation study, our aim is to investigate functional brain entropy as a biomarker for neonatal brain age. We have performed supervised machine learning based regression with the Developin