JMIR出版公司外包医疗数据分析:技术能克服法律、隐私和保密问题吗?卡塔尔世界杯8强波胆分析% Brumen, Bostjan %一个Heričko, Marjan %一个塞čnikar, Andrej %一个Završ尼克,Jernej % Holbl, Marko % +信息学研究所学院电气工程和计算机科学,马里博尔大学FERI G2, Smetanova 17日,马里博尔,2000年,斯洛文尼亚,386 2 2207292,marko.holbl@uni-mb.si % K保密% K病人数据隐私% K数据保护% K医疗决策% K计算机辅助% K数据分析% D原始论文7 16.12.2013 % 9 2013% % J J互联网Res % G英语% X背景:医学数据是获取知识的金矿，这些知识可以改变一个病人的生命进程，甚至是整个人口的健康。数据分析师需要完全访问相关数据，但医疗数据隐私和机密性法律法规可能会拒绝完全访问，特别是当数据分析师与数据所有者没有关联时。目标:我们的第一个目标是分析与医疗数据相关的隐私和保密问题以及相关法规，并确定适当解决这些问题的技术。我们的第二个目标是制定一种程序来保护医疗数据，使外包的分析人员能够对受保护的数据进行分析，其结果即使不相同，也可以与对原始数据进行的分析相比较。具体来说，我们的假设是建立在加密数据上的外包决策树和建立在原始数据上的外包决策树之间没有区别。方法:使用正式的定义，我们开发了一种算法来保护外包分析的医疗数据。该算法应用于医学和生命科学领域的公开数据集(N=30)。对原始数据集和保护数据集进行了分析，并对分析结果进行了比较。 Bootstrapped paired t tests for 2 dependent samples were used to test whether the mean differences in size, number of leaves, and the accuracy of the original and the encrypted decision trees were significantly different. Results: The decision trees built on encrypted data were virtually the same as those built on original data. Out of 30 datasets, 100% of the trees had identical accuracy. The size of a tree and the number of leaves was different only once (1/30, 3%, P=.19). Conclusions: The proposed algorithm encrypts a file with plain text medical data into an encrypted file with the data protected in such a way that external data analyses are still possible. The results show that the results of analyses on original and on protected data are identical or comparably similar. The approach addresses the privacy and confidentiality issues that arise with medical data and is adherent to strict legal rules in the United States and Europe regarding the processing of the medical data. %M 24342053 %R 10.2196/jmir.2471 %U //www.mybigtv.com/2013/12/e283/ %U https://doi.org/10.2196/jmir.2471 %U http://www.ncbi.nlm.nih.gov/pubmed/24342053