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Characterizing Normotypical Developmental Patterns in Early Childhood: An Exploratory Unsupervised Learning Study

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Embargado hasta 23/01/2028 (934.4Kb)
Author
Fernández-Merchán, Alberto
Alcalde-Llergo, José M.
Zingoni, Andrea
Sánchez-Raya, Araceli
Pérez-Dueñas, Carolina
Yeguas-Bolívar, Enrique
Publisher
IEEE
Date
2026
Subject
Machine learning
Clustering
Early childhood care
Neurodevelopmental disorders
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Abstract
This exploratory study investigates normative developmental patterns in early childhood using unsupervised learning techniques. Using data from 639 normotypically developing Spanish children (aged 1–84 months), we segment the population by age and apply clustering and dimensionality reduction to examine developmental trends. The analysis focuses on the most represented group (60–71 months), revealing modest cluster structure and meaningful inter-domain correlations. These results offer a data-driven reference for future early childhood screening efforts.
Description
Embargado hasta 23/01/2028
URI
http://hdl.handle.net/10396/35933
Fuente
A. Fernández-Merchán, J. M. Alcalde-Llergo, A. Zingoni, A. S. Raya, C. P. Dueñas and E. Yeguas-Bolívar, "Characterizing Normotypical Developmental Patterns in Early Childhood: An Exploratory Unsupervised Learning Study," 2025 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), Ancona, Italy, 2025, pp. 836-841.
Versión del Editor
http://dx.doi.org/10.1109/MetroXRAINE66377.2025.11340307
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