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Applications of data mining in healthcare area: A survey

机译:数据挖掘在医疗领域的应用:调查

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Data mining is the modern way of discovering knowledge among databases that leads to statistical analysis, pattern recognition, and information prediction. Today, one of the most important applications of data mining is in the healthcare field which leads to many advances in this area in order to increase the effectiveness of treatments, reduce the risks, decrease the costs, better patient relationships, early disease diagnosis, and etc. This article attempts to provide a comprehensive overview with a new classification of services that data mining has created or facilitated in the healthcare field. It includes disease diagnosis, early detection of diseases, managing pandemic diseases, dimension reduction, health monitoring, treatment effectiveness, system biology, management of hospital resources, hospital ranking, customer relationship management, public health policy planning, fraud and abuse detection, and control data overload. Furthermore, the strengths and weaknesses of data mining in the healthcare field are discussed and future directions in this area are mentioned. Finally, it can be concluded that although data mining has abundant applications in the healthcare area, especially in the diagnosis and prediction of diseases and healthcare business, medical data mining is still young and needs more attention.
机译:数据挖掘是在导致统计分析,模式识别和信息预测的数据库中发现知识的现代方法。今天,数据采矿的最重要应用之一就在医疗领域,这导致该地区的许多进展,以提高治疗的有效性,降低风险,降低成本,更好的患者关系,早期疾病诊断,以及本文试图提供全面的概述,并在医疗领域创造或促进了数据挖掘的新的服务分类。它包括疾病诊断,早期检测疾病,管理大流行病,维度减少,健康监测,治疗效果,系统生物学,医院资源管理,医院排名,客户关系管理,公共卫生政策规划,欺诈和滥用检测,以及控制数据过载。此外,讨论了医疗领域中的数据挖掘的强度和弱点,并提到了该地区的未来方向。最后,可以得出结论,尽管数据挖掘在医疗领域具有丰富的应用,但特别是在疾病和医疗保健业务的诊断和预测中,医疗数据挖掘仍然年轻,需要更多关注。

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