Ankle Injury Prevention In Soccer Using Machine Learning: Bibliometric Analysis

Abstract

Bibliometric analysis seeks to evaluate through statistical
methods the scientific activity on the lines and trends
of research, the evolution of studies, the relationships
between publications, journals and collaboration between
researchers. The use of these studies can guide researchers
on the evolution of research processes related to injury
prevention in soccer, using machine learning. The aim
of this study is to analyze the scientific activity related to
machine learning in the prevention of ankle injuries in
soccer. The present study presents three moments: Data
capture, Analysis of the information based on software
(Scimat, VosViewer, Use of Text mining with R), discussion
and conclusions. As for the results, the evolution of the
words and networks generated shows an increase in
studies relating the words “sport”, “ankle”, “risk factors” and “technology” (mobile applications, computational methods, wireless communication). An evolution of research in terms of the use of machine learning in injury prevention, visualization of knowledge networks and support among researchers in recent years is evident, as well as the growth of publications and the increase of networks and interaction between words.