Machine Learning Applied to Neuroreabilitation: A Systematic Mapping

F. G. Fernandes, Eder Santana
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Abstract

Machine learning and recommendation systems are tools used to improve the search indices of the most relevant items in large amounts of data that can be applied in the health area. To present a systematic mapping in the area of neurorehabilitation that uses machine learning. Analyze the references of the work carried out involving the theme on the application of machine learning in the area of neurorehabilitation. Search for studies enrolled in databases through logical operators for the selection of peer-reviewed journal articles. In addition, it was verified that the application of the systematic mapping in the elaboration of the bibliographic review allows to identify the main gaps for the development of new research, and to direct to the main publications related to the study. Therefore, it is necessary to promote this area of research to offer this public access to the techniques of neuro-rehabilitation as a form of treatment, acquisition of knowledge, motivation or even inclusion. In this way, it will be possible to obtain a greater maturity in the obtained results and, thus, to promote a systematization in the use of neuro-rehabilitation in the promotion of the well-being of these people.
机器学习在神经康复中的应用:一个系统的映射
机器学习和推荐系统是用于改进可应用于卫生领域的大量数据中最相关项目的搜索索引的工具。在神经康复领域使用机器学习呈现一个系统的地图。分析机器学习在神经康复领域应用这一主题所开展工作的参考文献。通过逻辑运算符搜索数据库中登记的研究,以选择同行评审的期刊文章。此外,经核实,在编制书目审查时采用系统的制图方法,可查明发展新研究的主要差距,并可指向与该研究有关的主要出版物。因此,有必要促进这一领域的研究,为公众提供神经康复技术作为一种治疗、获取知识、动力甚至包容的形式。这样,就有可能在取得的结果中获得更大的成熟度,从而促进在促进这些人的福祉中使用神经康复的系统化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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