Data Aggregation and Analysis for Cancer Statistics - A Visual Analytics Approach

The disparity between data collected in rural and urban counties is often detrimental in the appropriate analysis of cancer care statistics. Low counts drastically affect the incidence and mortality rates of the data, leading to skewed statistics. In order to more accurately report the data, various levels of aggregation have been used (grouping counties by population, age percentages, etc.); however, such data aggregation methods have often been ad hoc and/or time consuming. Such groupings are performed on a user defined basis; however, grouping based purely on population demographics does not take into account the spatial relationships between data. Furthermore, researchers want to search for spatiotemporal correlations within their data domain. In this work, we introduce a visual analytics system for exploring cancer care statistics in a series of linked views and interactive user interface queries. We also apply the AMOEBA algorithm [1] for clustering counties based on population...

• Type: Conference
• Year: 2010
• Where: HICSS
• Authors: Ross Maciejewski, Travis Drake, Stephen Rudolph, Abish Malik, David S. Ebert
• Keywords: Biometrics, Cancer Care Statistics, Data Aggregation, HICSS 2010, Population Demographics, System Sciences