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Design of Individual Physical Examination Package Based on Data Mining

Author: ZhanYin
Tutor: JinXinZheng
School: Huazhong University of Science and Technology
Course: Information Science
Keywords: data mining physical examination package clustering decision tree association rules
CLC: TP311.13
Type: Master's thesis
Year: 2010
Downloads: 90
Quote: 1
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Abstract


Background: Periodic health examination is an effective way for disease prevention and control, known as the fifth foundation of health. At present, there are many problems in the process of physical examination industry development, such as the institution of physical examination not clear, the service provided monotonous and the quality spotty. Besides, the physical examination package public demanded prevails the phenomenon of repeating at low level, pricing chaos and items superfluous.Objective: The aim of this study was to investigate the different kinds of customers’demands for physical examination and examination package, and design individual physical examination package for them, with data mining technology and questionnaire method.Methods: Random sampling method was taken to sample 228 participants in Luohu district Shenzhen city. Investigation on satisfaction to physical examination package was carried out. The analysis of questionnaire uses Microsoft office Excel. Collect Data of 34,224 person-trips taken physical examination in the physical examination center of a Shenzhen hospital in 2009. K-Means clustering model, C5.0 decision tree model, Apriori association rules model based on these data was contributed with data mining software Clementine 11.1.Results: Statistics suggest that accounting for 42.7 percent were not satisfied with the existing physical examination packages, 52.8 percent willing to take the packages at CNY 300~500 Yuan, 38.3 percent and 36.6 percent was satisfied with the 10~20 items and 20~30 items in the packages. K-Means clustering model divided 34,224 person-trips into 6 cluster based on the examination items and cost, C5.0 decision tree model summarized the rules of the customers’gender and age from the 6 cluster, Apriori association rule model studied all the association rules between different examination items. Finally, 9 kinds of physical examination packages were designed for different ages and gender people based on data mining technology and questionnaires method.Conclusion: This research first proposed design of physical examination package based on data mining technology; take a reasonable attempt in the innovation design of package; provide a viable idea for package design; promote the physical examination information system and data mining technology widely used in the healthy industry. This research used Clementine 11.1 software to construct physical examination data analysis model and stream of physical examination package designing, which can use for reference.The innovation of this study include: first proposed design of physical examination package based on data mining technology; first used Clementine 11.1 software to construct stream of physical examination package designing and 9 kinds of physical examination packages for different kinds of people, which there is not related research reports at home and abroad.The shortcomings of this research are lack of data and single of source, which reduced reliability and application scope of the results of data mining. The next step is to verify the packages in the medical theory and clinical practice.

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