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Important variable selection techniques with multiple solutions for medical information applications.

机译:重要的变量选择技术以及针对医疗信息应用的多种解决方案。

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The purpose of this study is to utilize the strategy of multiple solutions with easily operated tools to make compatible and affordable trustworthy results. This strategy can satisfy general users in extracting specific knowledge (e.g. diagnosis, treatment, health education, hospital administration, etc.). Wide application is one of the key promoters of a successful medical information system. Risk factors of heart disease can be identified by important variable selection techniques. Four techniques, Chi-square test, correlation analysis, stepwise discriminant analysis, and decision trees, were used in this study. One must compile the results of the different methods to deal with specific research questions in a logical way. It is expected that this approach may reduce the uncertainties obtained from a single method. When applying the important index derived from the four different method results to several applications, all results have been confirmed by current medical knowledge or otherwise provide meaningful information. The prime purpose of this study is not disease diagnosis, but to enable the general health practitioner (medical doctor, hospital administrator, etc.) to formulate their hypothesis.
机译:这项研究的目的是利用易于操作的工具采用多种解决方案的策略,以取得兼容且价格合理的可信赖结果。该策略可以满足一般用户在提取特定知识(例如诊断,治疗,健康教育,医院管理等)方面的要求。广泛的应用是成功医疗信息系统的关键推动者之一。心脏病的危险因素可以通过重要的变量选择技术来识别。本研究使用卡方检验,相关分析,逐步判别分析和决策树这四种技术。必须合乎逻辑地处理不同方法的结果,以处理特定的研究问题。预期该方法可以减少从单一方法获得的不确定性。当将源自四种不同方法结果的重要指标应用于多种应用时,所有结果均已被当前医学知识所确认,或者提供了有意义的信息。这项研究的主要目的不是疾病诊断,而是使普通保健医生(医生,医院管理人员等)能够提出其假设。

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