hrp0089p2-p236 | GH & IGFs P2 | ESPE2018

Artificial Neural Networks for Prediction Final Height in Children with growth Hormone Deficiency

Gavrilova Anna , Nagaeva Elena , Rebrova Olga , Shiryaeva Tatiana , Peterkova Valentina

Background: Mathematical models predicting final height (FH) and its standard deviation score (SDS) in children with growth hormone deficiency is an important tool for clinicians to manage treatment process. Previously developed models do not have enough accuracy or are not good enough for practical use.Objective and hypotheses: We used four binary and seven continuous predictors available at the time of diagnosis and start of therapy and developed multi...