Predictie van groei vanaf jonge leeftijd

Curve matching is a new big data technique to predict an outcome given earlier measurements. Here we apply curve matching to predict the future growth of a specific child, the target child. The method searches in large datasets of longitudinal growth data for other children who are similar to the target child in terms of factors that influence growth. The observed growth curves of these matched children provide valuable insights into the future growth of the target child. The TNO Groeivoorspeller (TNO Growth Predictor) plots the expected growth of the target child, as well as the uncertainty of the prediction. Curve matching is a general technique that can also be used for other health measures. The key requirement is the availability of relevant longitudinal data on the outcome and its determinants.

Conflict of interest and financial support for this article: S. van Buuren and M.P. L’Hoir received a research grant from TNO for building the demonstrator; S.A. Reijneveld received research grants for the LOLLIPOP study upon which the analyses were partially built from the research foundation of the Beatrix Children’s Hospital, the Cornelia Foundation for the Handicapped Child, the A. Bulk-Child Preventive Child Health Care Research Fund and the Dutch Brain Foundation, and unrestricted investigator-initiated research grants from FrieslandCampina, Friso Nederland, Abbott and Pfizer Europe. ICMJE forms provided by the authors are available online along with the full text of this article.