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Access, Handling and Visualization Tools for Multiple Data Types for Breast Cancer Decision Support

  • Breast cancer is the most commonly diagnosed cancer among U.S women, besides skin cancer. More than 1 in 4 cancers among women are breast cancer. And though death rates have been decreasing since 1990, about 40,170 women in the U.S. were expected to die in 2009 from breast cancer. The progress of molecular profiling, in the last decade has revolutionized the understanding of cancer, but also introduced more complexity with new data such as gene expression, copy number variation, mutations and DNA methylation. These new data open up the possibility of differential diagnosis, much more precise prognosis as well as prediction of therapy response than any of the diagnostic tools that are available in the current practice. Additionally, epidemiological databases store clinically relevant information on hundreds of thousands of patients. However, with the abundance of all this information, clinicians will need new tools to access and visualize such data and use the information gained to treat new patients. The general problem will be to access, filter and analyze the data and then visualize them in a clinical context. This data ranges from clinico-pathological information, to molecular profiles from highthroughput genomic measurements and imaging data. Furthermore, data from patient populations is aggregated on epidemiological level and can be found under numerous clinical studies.

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Author:Christian Reichelt
Document Type:Master's Thesis
Year of Completion:2011
Publishing Institution:Hochschule Heilbronn
Release Date:2011/10/14
Tag:Visualization ; Cancer ; Support
GND Keyword:Entscheidung; Handhabung
Faculty:Informatik / Medizinische Informatik
DDC classes:000 Allgemeines, Informatik, Informationswissenschaft / 000 Allgemeines, Wissenschaft / 004 Informatik
Access Right:Frei zugänglich
Licence (German):License LogoVeröffentlichungsvertrag für Publikationen mit Print on Demand