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Original scientific paper

https://doi.org/10.17559/TV-20210903062509

Internet Medical Privacy Disclosure Mining and Prediction Model Construction Based on Association Rules

Yong Wang ; School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China


Full text: english pdf 542 Kb

page 231-238

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Abstract

In recent years, China's Internet medical industry has developed rapidly and the market scale has been expanding. Medical privacy is an important research point in the Internet medical field. If the patient cannot fully communicate with the doctor on the other end of the Internet, then it is obvious that the patient will not be well treated. Then it becomes very worthwhile to mine the factors affecting patients' privacy disclosure and predict patients' disclosure behavior. This paper uses the classical and improved multidimensional Apriori (MD-Apriori) to mine patient privacy disclosure factors, which proves that the improved MD-Apriori algorithm is more applicable in this study. In order to prove the validity and authority of the mining results, this paper uses SPSS to analyze 331 valid questionnaires. The results show that the privacy disclosure factors obtained by the two methods are almost the same. Finally, based on the above factors, we establish the Internet medical privacy disclosure intention prediction model, in order to guide the construction and improvement of internet medical.

Keywords

internet medical; internet medical privacy disclosure intention prediction model; MD-Apriori (multi-dimensional Apriori); questionnaire; SPSS

Hrčak ID:

269504

URI

https://hrcak.srce.hr/269504

Publication date:

15.2.2022.

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