Abstract
In epidemiological cancer registries, extensive measures to clean data are inevitable. This is due to the heterogenity of reporting organizations, as for example hospitals, oncological centers, and physicians. Data cleansing ensures data quality, which is essential for epidemiological analysis and interpretation. By means of the software tool CARELIS, this paper shows that the process of data cleansing can be automatized to a considerable extent. CARELIS integrates a probabilistic record linkage method with knowledge-based techniques to minimize the effort of manual after-treatment of notifications transmitted to the registry. This paper focusses the discussion of experiences made by CARELIS users, usually medical documentation assistants.
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© 1999 Springer-Verlag Berlin Heidelberg
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Hinrichs, H., Panienski, K. (1999). Experiences with Knowledge-Based Data Cleansing at the Epidemiological Cancer Registry of Lower-Saxony. In: Puppe, F. (eds) XPS-99: Knowledge-Based Systems. Survey and Future Directions. XPS 1999. Lecture Notes in Computer Science(), vol 1570. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10703016_18
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DOI: https://doi.org/10.1007/10703016_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-65658-6
Online ISBN: 978-3-540-49149-1
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