Commenced in January 2007
Paper Count: 31023
Automatic Real-Patient Medical Data De-Identification for Research Purposes
Authors: Petr Vcelak, Jana Kleckova
Abstract:Our Medicine-oriented research is based on a medical data set of real patients. It is a security problem to share patient private data with peoples other than clinician or hospital staff. We have to remove person identification information from medical data. The medical data without private data are available after a de-identification process for any research purposes. In this paper, we introduce an universal automatic rule-based de-identification application to do all this stuff on an heterogeneous medical data. A patient private identification is replaced by an unique identification number, even in burnedin annotation in pixel data. The identical identification is used for all patient medical data, so it keeps relationships in a data. Hospital can take an advantage of a research feedback based on results.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1062696Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1296
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