{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T03:32:39Z","timestamp":1762054359400,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,5,27]],"date-time":"2022-05-27T00:00:00Z","timestamp":1653609600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"co-funded by the EUROPEAN UNION","award":["2021-1-ES01-KA220-SCH-9A787316"],"award-info":[{"award-number":["2021-1-ES01-KA220-SCH-9A787316"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>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\u20136 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\u2019 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.<\/jats:p>","DOI":"10.3390\/ijerph19116558","type":"journal-article","created":{"date-parts":[[2022,5,28]],"date-time":"2022-05-28T01:40:45Z","timestamp":1653702045000},"page":"6558","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Improvements for Therapeutic Intervention from the Use of Web Applications and Machine Learning Techniques in Different Affectations in Children Aged 0\u20136 Years"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1736-2089","authenticated-orcid":false,"given":"Mar\u00eda Consuelo","family":"S\u00e1iz-Manzanares","sequence":"first","affiliation":[{"name":"Research Group DATAHES, Departamento de Ciencias de la Salud, Facultad de Ciencias de la Salud, Universidad de Burgos, P\u00ba Comendadores s\/n, 09001 Burgos, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2633-635X","authenticated-orcid":false,"given":"Ra\u00fal","family":"Marticorena-S\u00e1nchez","sequence":"additional","affiliation":[{"name":"Research Group ADMIRABLE, Departamento de Ingenier\u00eda Inform\u00e1tica, Escuela Polit\u00e9cnica Superior, Universidad de Burgos, Avd. de Cantabria s\/n, 09006 Burgos, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"\u00c1lvar","family":"Arnaiz-Gonz\u00e1lez","sequence":"additional","affiliation":[{"name":"Research Group ADMIRABLE, Departamento de Ingenier\u00eda Inform\u00e1tica, Escuela Polit\u00e9cnica Superior, Universidad de Burgos, Avd. de Cantabria s\/n, 09006 Burgos, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,27]]},"reference":[{"key":"ref_1","first-page":"1659","article-title":"Enhanced Approaches in Decision Support System Using Ai for Achieving Precision Medicine","volume":"9","author":"Kumar","year":"2020","journal-title":"Int. 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