2026-05-23T07:32:40Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/73402023-03-21T10:52:15Zcom_10259_5841com_10259_5086com_10259_2604com_10259_4219col_10259_5842col_10259_4220
Improvements for Therapeutic Intervention from the Use of Web Applications and Machine Learning Techniques in Different Affectations in Children Aged 0–6 Years
Sáiz Manzanares, María Consuelo
Marticorena Sánchez, Raúl
Arnaiz González, Álvar
Early care
Web application
Machine learning techniques
Precision therapeutic program
Personalized intervention
Disabilities
Technological advances together with machine learning techniques give health science
disciplines tools that can improve the accuracy of evaluation and diagnosis. The objectives of this
study were: (1) to design a web application based on cloud technology (eEarlyCare-T) for creating
personalized therapeutic intervention programs for children aged 0–6 years old; (2) to carry out a
pilot study to test the usability of the eEarlyCare-T application in therapeutic intervention programs.
We performed a pilot study with 23 children aged between 3 and 6 years old who presented a
variety of developmental problems. In the data analysis, we used machine learning techniques of
supervised learning (prediction) and unsupervised learning (clustering). Three clusters were found in
terms of functional development in the 11 areas of development. Based on these groupings, various
personalized therapeutic intervention plans were designed. The variable with most predictive value
for functional development was the users’ developmental age (predicted 75% of the development
in the various areas). The use of web applications together with machine learning techniques
facilitates the analysis of functional development in young children and the proposal of personalized
intervention programs.
2023-01-26
2023-01-26
2022-05
info:eu-repo/semantics/article
http://hdl.handle.net/10259/7340
10.3390/ijerph19116558
1660-4601
eng
International Journal of Environmental Research and Public Health. 2022, V. 19, n. 11, 6558
https://doi.org/10.3390/ijerph19116558
info:eu-repo/grantAgreement/EC/Erasmus+/2021-1-ES01-KA220-SCH-9A787316/EU/Specialized and updated training on supporting advance technologies for early childhood education and care professionals and graduates/eEarlyCare-T/
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
Atribución 4.0 Internacional
MDPI