{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T13:37:59Z","timestamp":1761745079188,"version":"build-2065373602"},"reference-count":47,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2019,12,12]],"date-time":"2019-12-12T00:00:00Z","timestamp":1576108800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008447","name":"CIT","doi-asserted-by":"publisher","award":["This work has been partially supported by Portuguese National funds through FITEC programa Interface, with reference CIT \u201cINOV\u2014INESC Inova\u00e7\u00e3o\u2014Financiamento Base\u201d."],"award-info":[{"award-number":["This work has been partially supported by Portuguese National funds through FITEC programa Interface, with reference CIT \u201cINOV\u2014INESC Inova\u00e7\u00e3o\u2014Financiamento Base\u201d."]}],"id":[{"id":"10.13039\/501100008447","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>This study is a contribution for the improvement of healthcare in children and in society generally. This study aims to predict children\u2019s height when they become adults, also known as \u201ctarget height\u201d, to allow for a better growth assessment and more personalized healthcare. The existing literature describes some existing prediction methods, based on longitudinal population studies and statistical techniques, which with few information resources, are able to produce acceptable results. The challenge of this study is in using a new approach based on machine learning to forecast the target height for children and (eventually) improve the existing height prediction accuracy. The goals of the study were achieved. The extreme gradient boosting regression (XGB) and light gradient boosting machine regression (LightGBM) algorithms achieved considerably better results on the height prediction. The developed model can be usefully applied by pediatricians and other clinical professionals in growth assessment.<\/jats:p>","DOI":"10.3390\/app9245447","type":"journal-article","created":{"date-parts":[[2019,12,12]],"date-time":"2019-12-12T11:06:41Z","timestamp":1576148801000},"page":"5447","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Child\u2019s Target Height Prediction Evolution"],"prefix":"10.3390","volume":"9","author":[{"given":"Jo\u00e3o Rala","family":"Cordeiro","sequence":"first","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es, IT-IUL, Instituto Universit\u00e1rio de Lisboa, ISCTE-IUL, 1649-026 Lisbon, Portugal"}]},{"given":"Octavian","family":"Postolache","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es, IT-IUL, Instituto Universit\u00e1rio de Lisboa, ISCTE-IUL, 1649-026 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6662-0806","authenticated-orcid":false,"given":"Jo\u00e3o C.","family":"Ferreira","sequence":"additional","affiliation":[{"name":"INOV INESC Inova\u00e7\u00e3o\u2014Instituto de Novas Tecnologias, 1000-029 Lisbon, Portugal"},{"name":"Instituto Superior T\u00e9cnico, 1049-001 Lisbon, Portugal"},{"name":"ISTAR-IUL, Instituto Universit\u00e1rio de Lisboa (ISCTE-IUL), 1649-026 Lisbon, Portugal"},{"name":"Centro ALGORITMI, University of Minho, 4800-058 Guimar\u00e3es, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1603","DOI":"10.1017\/S136898001200105X","article-title":"Worldwide implementation of the WHO Child Growth Standards","volume":"15","author":"Onyango","year":"2012","journal-title":"Public Health Nutr."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1016\/S0140-6736(07)61692-4","article-title":"Maternal and child undernutrition. 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