临床医学中的预测数据挖掘:当前问题和指南

Joey G. Fernando, Dr. Sanjiv Kumar Jain
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引用次数: 3

摘要

下面的研究是基于临床医学的预测数据挖掘,所有的数据都是围绕以下主题选择的。本文首先简要介绍了数据挖掘、预测数据挖掘及其在临床医学中的应用。然后提供了所需的材料和方法。然后阐述了预测数据挖掘在临床医学中的应用。在几个部分中描述了其用法,例如预测数据挖掘在临床药物中的使用。此外,还以广泛的方式说明了预测数据挖掘的不同模型的使用。稍后,预测数据挖掘对医疗保健部门的好处及其为医疗从业者使用预测数据挖掘的利润和优势已通过收集有效的见解来表示。此外,与医疗保健部门和临床药物相关的挑战和问题已经在以下研究中得到了炫耀,并且通过使用预测数据挖掘来缓解问题的策略已经被详细描述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Data Mining in Clinical Medicine: Current Issues and Guidelines
The following study is based on the predictive data mining in clinical medicine where all data have been selected by focusing on the following topic. At the first the brief introduction of data mining, predictive data mining and its usage on the clinical medicines have been shared. Then the required materials and methods have been furnished up next. After that, the usages of predictive data mining in clinical medicines have been elaborated. The usages have been depicted within several parts of, such the use of predictive data mining in the clinical medicines. Also, the uses of different models of predictive data mining have been illustrated within an extensive manner. Later on, the benefits of predictive data mining for the healthcare sector and its profit making and advantages for using predictive data mining for a medical practitioner have been represented by gathering valid insights. Furthermore, the challenges and issues related to healthcare sectors and clinical medicines have ben flaunted in the following study and the strategies to mitigate the problems by using predictive data mining has been depicted within sheer elaboration.
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