Visual Computing for Big Data Analysis in Prostate Cancer Research
| dc.contributor.author | Bernard, Jürgen | en_US |
| dc.contributor.author | May, Thorsten | en_US |
| dc.contributor.author | Pehrke, Dirk | en_US |
| dc.contributor.author | Schlomm, Thorsten | en_US |
| dc.contributor.author | Kohlhammer, Jörn | en_US |
| dc.contributor.editor | Stefan Bruckner and Timo Ropinski | en_US |
| dc.date.accessioned | 2017-04-22T16:59:07Z | |
| dc.date.available | 2017-04-22T16:59:07Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | Data-centered research is becoming increasingly important in prostate cancer research where a long-term goal is a sound prognosis prior to surgery. We have developed a visual computing technology that contributes to this paradigm change in clinical research and practice for electronic health records (EHR) in this area. This visual-interactive system, developed in close collaboration with medical researchers, helps clinicians efficiently and effectively visualize single and multiple patient histories at a glance, create cohorts of patients for clinical tests, as well as generate and validate hypotheses. | en_US |
| dc.description.sectionheaders | 3rd Prize | |
| dc.description.seriesinformation | EG 2017 - Dirk Bartz Prize | |
| dc.identifier.doi | 10.2312/egm.20171044 | |
| dc.identifier.issn | 1017-4656 | |
| dc.identifier.pages | 9-13 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/egm20171044 | |
| dc.identifier.uri | https://doi.org/10.2312/egm.20171044 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.title | Visual Computing for Big Data Analysis in Prostate Cancer Research | en_US |