Suki, Béla and Frey, Urs. (2017) A time-varying biased random walk approach to human growth. Scientific Reports, 7 (1). p. 7805.
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Official URL: https://edoc.unibas.ch/82180/
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Abstract
Growth and development are dominated by gene-environment interactions. Many approaches have been proposed to model growth, but most are either descriptive or describe population level phenomena. We present a random walk-based growth model capable of predicting individual height, in which the growth increments are taken from time varying distributions mimicking the bursting behaviour of observed saltatory growth. We derive analytic equations and also develop a computational model of such growth that takes into account gene-environment interactions. Using an independent prospective birth cohort study of 190 infants, we predict height at 6 years of age. In a subset of 27 subjects, we adaptively train the model to account for growth between birth and 1 year of age using a Bayesian approach. The 5-year predicted heights compare well with actual data (measured height = 0.838*predicted height + 18.3; R; 2; = 0.51) with an average error of 3.3%. In one patient, we also exemplify how our growth prediction model can be used for the early detection of growth deficiency and the evaluation of the effectiveness of growth hormone therapy.
Faculties and Departments: | 03 Faculty of Medicine > Bereich Kinder- und Jugendheilkunde (Klinik) > Kinder- und Jugendheilkunde (UKBB) > Pädiatrie (Frey) 03 Faculty of Medicine > Departement Klinische Forschung > Bereich Kinder- und Jugendheilkunde (Klinik) > Kinder- und Jugendheilkunde (UKBB) > Pädiatrie (Frey) |
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UniBasel Contributors: | Frey, Urs Peter |
Item Type: | Article, refereed |
Article Subtype: | Research Article |
Publisher: | Nature Publishing Group |
e-ISSN: | 2045-2322 |
Note: | Publication type according to Uni Basel Research Database: Journal article |
Language: | English |
Identification Number: |
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edoc DOI: | |
Last Modified: | 03 Mar 2021 11:38 |
Deposited On: | 03 Mar 2021 11:38 |
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