Clinical Data Warehouse Watermarking: Impact on Syndromic Measure

Guillaume Bouzille (1, 2) , Wei Pan (3, 4) , Javier Franco-Contreras (3, 4) , Marc Cuggia (5, 1) , Gouenou Coatrieux (4)

1 LTSI - Laboratoire Traitement du Signal et de l'Image
2 CIC - Centre d'Investigation Clinique [Rennes]
3 ITI - Département Image et Traitement Information
4 LaTIM - Laboratoire de Traitement de l'Information Medicale
5 CIC-IT Rennes

Watermarking appears as a promising tool for the traceability of shared medical databases as it allows hiding the traceability information into the database itself. However, it is necessary to ensure that the distortion resulting from this process does not hinder subsequent data analysis. In this paper, we present the preliminary results of a study on the impact of watermarking in the estimation of flu activities. These results show that flu epidemics periods can be estimated without significant perturbation even when considering a moderate watermark distortion.

Mots clés: Clinical data warehouse; Traceability; Watermarking

Domaines: Ingénierie biomédicale

Guillaume Bouzille, Wei Pan, Javier Franco-Contreras, Marc Cuggia, Gouenou Coatrieux. Clinical Data Warehouse Watermarking: Impact on Syndromic Measure. Studies in Health Technology and Informatics, 2017, 235, pp.323-327. ⟨10.3233/978-1-61499-753-5-323⟩. ⟨hal-01518405⟩