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Generation of Fine Grained Demographic Information for Epidemiological Analysis
2020
Studies in Health Technology and Informatics
Cancer risks may be influenced by local exposures such as working conditions or nuclear waste repositories. To find influences, local accumulations of cancer rates are used, for which finely granulated data should be utilized. In particular, high-resolution demographic data for a reference population are important, but often not available for data protection reasons. Therefore, estimation methods are necessary to approximate small-scale demographic data as accurately as possible. This paper
doi:10.3233/shti200157
pmid:32570381
fatcat:dwp4qcatl5fhnbvg6zjslkrdqm