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首页> 外文会议>2018 5th International Conference on Business and Industrial Research >Association rules to analyze hospital resources with mortality rates
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Association rules to analyze hospital resources with mortality rates

机译：协会规则以死亡率分析医院资源

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摘要

According to the number of mortality from public health statistics data of the Strategy and Planning Division, the Permanent Secretary Office (1977 - 2014) had been increasing consecutively every year, so health service is the most important task to reduce the mortality rate for the Thai population. The purpose of this paper is to show an association between mortality and health service by using Apriori algorithm and FP-growth algorithm. We found the number of government hospitals with patient beds 13.29-15.90, 1350.44-1540.58 patient beds, 107-216 doctors, 15-30 dentists, 18-46 pharmacists, 271-625 nurses and 321-417 technical nurses per 1 million populations have a relationship to the number of deaths at very low rates and the result of data mining technique found both Apriori algorithm and FP-growth algorithm had similarly result but rule number and discrepancy analyzed.
机译：根据战略和计划部公共卫生统计数据中的死亡率，常任秘书长办公室（1977年至2014年）每年都在连续增加，因此，卫生服务是降低泰国死亡率的最重要任务人口。本文的目的是通过使用Apriori算法和FP-growth算法来显示死亡率与医疗服务之间的关联。我们发现每100万人口中拥有病床13.29-15.90，病床1350.44-1540.58，政府107-216医生，15-30牙医，18-46药剂师，271-625护士和321-417技术护士的政府医院数量与极低死亡率下的死亡人数之间的关系以及数据挖掘技术的结果发现，Apriori算法和FP-growth算法的结果相似，但分析了规则数量和差异。

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