Autor según el artículo: Moreno-García C; Aceves-Martins M; Serratosa F
Departamento: Enginyeria Informàtica i Matemàtiques
Autor/es de la URV: ACEVES MARTINS, MAGALY / MORENO GARCIA, CARLOS FRANCISCO / Serratosa Casanelles, Francesc d'Assís
Palabras clave: Unsupervised machine learning Systematic review Recommender systems Principal component analysis Primer Prevention Physical-activity Middle-income countries Meta-analysis Interventions
Resumen: When trying to synthesize information from multiple sources and perform a statistical review to compare them, particularly in the medical research field, several statistical tools are available, most common are the systematic review and the meta-analysis. These techniques allow the comparison of the effectiveness or success among a group of studies. However, a problem of these tools is that if the information to be compared is incomplete or mismatched between two or more studies, the comparison becomes an arduous task. On a parallel line, machine learning methodologies have been proven to be a reliable resource, such software is developed to classify several variables and learn from previous experiences to improve the classification. In this paper, we use unsupervised machine learning methodologies to describe a simple yet effective algorithm that, given a dataset with missing data, completes such data, which leads to a more complete systematic review and metaanalysis, capable of presenting a final effectiveness or success rating between studies. Our method is first validated in a movie ranking database scenario, and then used in a real life systematic review and metaanalysis of obesity prevention scientific papers, where 66.6% of the outcomes are missing.
Áreas temáticas: Interdisciplinar General computer science Engenharias iii Computer science, information systems Computer science (miscellaneous) Computer science (all) Ciencias sociales
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
Direcció de correo del autor: francesc.serratosa@urv.cat
Identificador del autor: 0000-0001-6112-5913
Fecha de alta del registro: 2024-06-22
Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
Enlace a la fuente original: https://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/2360
URL Documento de licencia: http://repositori.urv.cat/ca/proteccio-de-dades/
Referencia al articulo segun fuente origial: Computacion Y Sistemas. 20 (1): 7-17
Referencia de l'ítem segons les normes APA: Moreno-García C; Aceves-Martins M; Serratosa F (2016). Unsupervised machine learning application to perform a systematic review and meta-analysis in medical research. Computacion Y Sistemas, 20(1), 7-17. DOI: 10.13053/CyS2012360
DOI del artículo: 10.13053/CyS-20-1-2360
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2016
Tipo de publicación: Journal Publications
Repositori URV