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Prediction model of sports injury based on dynamic sampling and transfer learning

机译：基于动态抽样和转移学习的运动损伤预测模型

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摘要

Injury frequently occurs in a team sport, important for athletes and their sports organizations, financial, physical, and psychological. Therefore, extensive studies, the risk of very important element damage when developing prevention and risk mitigation strategies of work-related accidents, trying to find. Many ways can be used to identify risk factors for injury. However, it made from data, it is difficult can lead to the erroneous inference, and decision making will understand the subtle differences between the different statistical methods. Such data conversion, as the verification and performance evaluation method of the model, the risk of injury, there are other important considerations at the time of modeling. Because of these technical considerations, researchers and practitioners, from the point of view to recover the army's cause, which is an active injury, should consider the complex. Simultaneously, research and implementation of the recovery method notify the complex methods to determine the risk of injury and need to be implemented. However, the ability to capture a large injury number is the current limit of sports injuries research. It is possible to verify to replicate the analysis and results. It emerged to provide researchers with data call to have. Such a concerted effort is, from making the wrong inference, to prevent incorrect data, will help to support the development of interventions supported by sound scientific evidence. These efforts risk injury, improve and thus risk reduction, and ultimately improve the ability to determine one step to help the right direction prevent injury.
机译：在团队运动中经常发生伤害，对于运动员及其体育组织，财务，身体和心理很重要。因此，广泛的研究，在制定有关事故的预防和风险缓解战略时，造成非常重要的因素损害的风险，试图找到。许多方式可用于识别伤害的危险因素。然而，它由数据制成，难以导致错误推断，决策将理解不同统计方法之间的微妙差异。这种数据转换，作为模型的验证和性能评估方法，伤害风险，在建模时存在其他重要的考虑因素。由于这些技术考虑因素，研究人员和从业者，从恢复军队的事业的角度来看，这是一个积极伤害，应该考虑复杂。同时，恢复方法的研究和实施通知复杂的方法来确定伤害的风险，需要实施。然而，捕获大伤害数量的能力是运动损伤研究的目前限制。可以验证是否复制分析和结果。它出现了提供数据调用的研究人员。这种协同努力是从制造错误的推理来防止错误数据，将有助于支持声音证据支持的干预措施的发展。这些努力风险伤害，改善和减少风险，最终提高确定一个步骤帮助正确方向的能力。

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  • 来源
    《Microprocessors and microsystems》 |2021年第2期|103583.1-103583.5|共5页
  • 作者

    Zhou Yi; Wu Xianwu; Li Xifeng;

  • 作者单位

    Guizhou Normal Univ Sch Phys Educ Guiyang 550001 Guizhou Peoples R China;

    Guizhou Normal Univ Sch Phys Educ Guiyang 550001 Guizhou Peoples R China;

    Huaihua Univ Coll Kinesiol & Hlth Sci Huaihua 418000 Hunan Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Injury; Performance evaluation; Sports injuries; Risk of injury;

    机译：伤害;绩效评估;体育伤害;受伤风险;

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