ESPE Yearbook of Paediatric Endocrinology

J Clin Endocrinol Metab. 2021; 16;106(7):e2700–e2710.PMID: 33606028 doi: 10.1210/clinem/dgab093This paper illustrates the power of machine learning to successfully predict adult height using growth measurements before age 6 years, without the need for bone age.Computers beat us in games of predictions, such as chess. They beat us also in the exercise of predictin...

Brief summary: Growth data from three independent longitudinal cohort studies (Gothenburg GrowUp 1974 (n 1596); Gothenburg GrowUp 1990 (n 1890); Edinburgh Growth Study (n 145)) were used to train machine learning (ML) to predict adult height (AH) based on growth measurements until the age of 6 years. Five ML algorithms were tested. A random forest model predicted best, with sex and height at age 3.4–6.0 years being the most influencing factors. The model was cross-validat...