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TsP-SA: usage of time series techniques on healthcare data

机译:TsP-SA:在医疗保健数据上使用时间序列技术

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摘要

In the recent years, there has been an increase in the usage of time series techniques on healthcare data. Although much effort has been made to develop techniques of time series, there is a lack of comprehensive categorisation of such techniques to make the possibility of exact study, comparison and assessment of techniques in terms of the ability predicting. We proposed time series prediction-strategy ahead (TsP-SA), a systematic framework which consists of the three main components: categorisation of time series prediction techniques in the context of healthcare, defining general evaluation criteria and analytical evaluation to illustrate a qualitative comparison between each category of techniques which is a proof of the understanding of their supremacy to one another. We believe that using proposed framework as a stimulus can help in the proper selecting technique, efficiency improvement, and development of techniques in researcher's future activities and can provide a helpful platform for the comparative study.
机译:近年来,在医疗保健数据上使用时间序列技术的情况有所增加。尽管已经为开发时间序列技术付出了很多努力,但仍缺乏对此类技术的全面分类,从而无法根据能力预测进行精确的研究,比较和评估。我们提出了提前时序预测策略(TsP-SA),它是一个由三个主要组成部分组成的系统框架:在医疗保健方面对时序预测技术进行分类,定义一般评估标准和分析评估,以说明两者之间的定性比较每种技术类别都是对它们至高无上的理解的证明。我们认为,使用拟议的框架作为刺激可以帮助研究人员未来的活动中选择合适的技术,提高效率和发展技术,并可以为比较研究提供有用的平台。

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