George Mathew
ABSTRACT
We model transactions as exchange of graphs and propose constraint graphs as transaction filters for attribute-based transformations in clinical settings. An informal representation and working of constraint graphs is presented. A workbench was developed using a real world EMR system to demonstrate the concept. Results of our experiments using constraint graphs are consistent with published benchmark results.
- Mathew, G and Obradovic, Z. 2011. A Privacy-Preserving Framework for Distributed Clinical Decision Support. In Proceedings of the 1st IEEE International Conference on Computational Advances in Bio and medical Sciences. Feb 2011, Orlando, FL. DOI=http://dx.doi.org/10.1109/ICCABS.2011.5729866 Google Scholar
Digital Library
- Aggarwal, C. C., and Wang, H. 2010. Managing and Mining Graph Data. Springer, NY, USA. Google ScholarDigital Library
- Dwork, C. 2006. Differential Privacy. In Proceedings of 33rd International Colloquium on Automata, Languages and Programming, July, 2006. Venice, Italy, pp. 1--12. Google ScholarDigital Library
- McSherry, F. D. 2009. Privacy integrated queries: an extensible platform for privacy-preserving data analysis. In Proceedings of the 35th SIGMOD International Conference on Management of Data, Providence, RI. pp. 19--30. DOI=http://dx.doi.org/10.1145/1559845.1559850. Google ScholarDigital Library
- He, H., and Singh, A. K. 2008. Graphs-at-a-time: Query Language and Access Methods for Graph Databases. In Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data. Vancouver, Canada. DOI=http://dx.doi.org/10.1145/1376616.1376660. Google ScholarDigital Library
- Home page for Open EMR software, 2010. http://www.oemr.org.Google Scholar
- SPECT Heart Data Set: Available at -- http://archive.ics.uci.edu/ml/datasets/SPECT+HeartGoogle Scholar
Index Terms
- Constraint graphs as security filters for privacy assurance in medical transactions
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