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                            [identifier] => oai:acimed.sld.cu:article/2470
                            [datestamp] => 2023-12-21T21:12:51Z
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                                    [title] => Array
                                        (
                                            [0] => Bibliometric Analysis of the Prediction of Lower Limb Injuries
                                            [1] => Análisis bibliométrico de la predicción de lesiones en miembros inferiores
                                        )

                                    [creator] => Array
                                        (
                                            [0] => Villaquiran-Hurtado, Andres Felipe
                                            [1] => Burbano Fernandez, Marlon Felipe
                                            [2] => Celis Quinayas, Viviana Marcela
                                            [3] => Hoyos-Quisoboni, Jeffry Alexander
                                        )

                                    [subject] => Array
                                        (
                                            [0] => bibliometrics; lower extremity; prediction; rehabilitation; machine learning.
                                            [1] => bibliometría; extremidad inferior; predicción; rehabilitación; aprendizaje automático.
                                        )

                                    [description] => Array
                                        (
                                            [0] => This article covers a bibliometric analysis on the prediction of lower extremity injuries. To achieve this, we started with a bibliographic search in Scopus and Web of Science databases from 2018 to 2022, using Boolean search strings. Document management software, text mining and systematic mapping were used to find global trends. Regarding the results, 4838 documents were taken into account. In the last five years there has been an interest in focusing research on words such as “machine learning”, “deep learning”, “rehabilitation”, “gait” and “electromyography”. When the focus is on the word “injury”, the network that is generated with the words “machine learning”, “injury prevention”, “prediction”, “running” and “knee” stands out. Regarding the prediction of lower extremity injuries, publications have increased over the last five years and focus their attention on patients for the application of data models based on control and rehabilitation. Focuses and networks are shown among the words “injury prevention”, “machine learning” and “rehabilitation”. Future research should focus efforts on determining the variability and specificity of machine learning processes used for prevention and control, taking into account the tissue, type of injury, area and joint affected.
                                            [1] => Este artículo realiza un análisis bibliométrico acerca de la predicción de lesiones en extremidades inferiores. Para ello se parte de una búsqueda bibliográfica en las bases de datos Scopus y Web of Science durante el período 2018-2022, utilizando cadenas booleanas de búsqueda. Se empleó un software de gestión documental, la minería de texto y un mapeo sistemático para encontrar las tendencias a nivel mundial. En cuanto a los resultados, se tuvieron en cuenta 4838 documentos. En los últimos cinco años existe un interés por centrar las investigaciones en palabras como “machine learning”, “deep learning”, “rehabilitation”, “gait” y “electromyography”. Cuando el foco es la palabra “injury” sobresale la red que se genera con las palabras: “machine learning”, “injury prevention”, “prediction”, “running” y “knee”. En lo que concierne a la predicción de lesiones de extremidades inferiores, las publicaciones han aumentado durante los últimos cinco años y centran su atención en los pacientes para la aplicación de modelos de datos en función del control y la rehabilitación. Se muestran focos de atención y redes entre las palabras “injury prevention”, “machine learning” y “rehabilitation”. Las investigaciones futuras deben centrar sus esfuerzos en determinar la variabilidad y la especificidad de los procesos de aprendizaje automático utilizados para la prevención y el control, teniendo en cuenta el tejido, el tipo de lesión, la zona y la articulación afectada.
                                        )

                                    [publisher] => ECIMED
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                                            [0] => SimpleXMLElement Object
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                                                )

                                            [1] => Universidad del Cauca
                                        )

                                    [date] => 2023-11-27
                                    [type] => Array
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                                            [0] => info:eu-repo/semantics/article
                                            [1] => info:eu-repo/semantics/publishedVersion
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                                        )

                                    [format] => application/pdf
                                    [identifier] => https://acimed.sld.cu/index.php/acimed/article/view/2470
                                    [source] => Array
                                        (
                                            [0] => Revista Cubana de Información en Ciencias de la Salud; Vol. 34 (2023): Publicación  continua
                                            [1] => 2307-2113
                                        )

                                    [language] => spa
                                    [relation] => Array
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                                            [0] => https://acimed.sld.cu/index.php/acimed/article/view/2470/pdf
                                            [1] => https://acimed.sld.cu/index.php/acimed/article/downloadSuppFile/2470/950
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                                        )

                                    [rights] => Array
                                        (
                                            [0] => Copyright (c) 2023 Andres Felipe Villaquiran Hurtado, Marlon Felipe Burbano Fernandez, Viviana Marcela Celis Quinayas, Jeffry Alexander Hoyos Quisoboni
                                            [1] => http://creativecommons.org/licenses/by-nc-sa/4.0
                                        )

                                )

                        )

                )

        )

)