Name
Abstract | ||
|---|---|---|
This paper presents a visual data mining approach using the combination of clinical data, pathways and gene-expression data. The visual exploration of medical data using pathways to navigate and filter the data allows a more systematic and efficient investigation of problems in modern life science. A multiplicity of hypothesis can be evaluated in the same period of time, enabling a much better exploitation of the data. We present a system for data preprocessing and automatic classification, a set of visualization views and finally the integration in the Caleydo visualization framework, which enables the ldquocouplingrdquo of genetic and a broad spectrum of clinical data. With the help of the Caleydo framework the medical expert can identify connections between genetic parameters, patient subgroups, and drug responses. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/IV.2009.86 | Barcelona |
Keywords | Field | DocType |
data mining,data visualisation,diseases,medical administrative data processing,Caleydo visualization framework,automatic classification,biomolecular data,clinical data,data preprocessing,gene-expression data,genetic coupling,visual data mining approach,Information Visualization,Medical Glyphs,Parallel Coordinates,Pathways | Data mining,Data visualization,Information visualization,Computer science,Visualization,Data pre-processing,Classification tree analysis,Parallel coordinates | Conference |
ISSN | ISBN | Citations |
1550-6037 | 978-0-7695-3733-7 | 3 |
PageRank | References | Authors |
0.44 | 12 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Heimo Müller | 1 | 358 | 28.60 |
| Reihs, R. | 2 | 5 | 0.84 |
| Sauer, S. | 3 | 5 | 0.84 |
| Zatloukal, K. | 4 | 3 | 0.44 |