David Gotz, Ph.D.
Affiliations: | 2005 | University of North Carolina, Chapel Hill, Chapel Hill, NC |
Area:
Computer ScienceGoogle:
"David Gotz"Parents
Sign in to add mentor| Ketan Mayer-Patel | grad student | 2005 | UNC Chapel Hill | |
| (Channel set adaptation: Scalable and adaptive streaming for non-linear media.) | ||||
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Publications
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| Borland D, Brain I, Fecho K, et al. (2021) Enabling Longitudinal Exploratory Analysis of Clinical COVID Data. Arxiv |
| Guo Y, Guo S, Jin Z, et al. (2021) Survey on Visual Analysis of Event Sequence Data. Ieee Transactions On Visualization and Computer Graphics |
| Guo S, Jin Z, Chen Q, et al. (2021) Interpretable Anomaly Detection in Event Sequences via Sequence Matching and Visual Comparison. Ieee Transactions On Visualization and Computer Graphics |
| Borland D, Zhang J, Kaul S, et al. (2020) Selection-Bias-Corrected Visualization via Dynamic Reweighting. Ieee Transactions On Visualization and Computer Graphics |
| Jin Z, Guo S, Chen N, et al. (2020) Visual Causality Analysis of Event Sequence Data. Ieee Transactions On Visualization and Computer Graphics |
| Kaul S, Coleman C, Gotz D. (2020) A rapidly deployed, interactive, online visualization system to support fatality management during the coronavirus disease 2019 (COVID-19) pandemic. Journal of the American Medical Informatics Association : Jamia |
| Coleman C, Gotz D, Eaker S, et al. (2020) Analysing EHR navigation patterns and digital workflows among physicians during ICU pre-rounds. Health Information Management : Journal of the Health Information Management Association of Australia. 1833358320920589 |
| Gotz D, Zhang J, Wang W, et al. (2019) Visual Analysis of High-Dimensional Event Sequence Data via Dynamic Hierarchical Aggregation. Ieee Transactions On Visualization and Computer Graphics |
| Borland D, Wang W, Zhang J, et al. (2019) Selection Bias Tracking and Detailed Subset Comparison for High-Dimensional Data. Ieee Transactions On Visualization and Computer Graphics |
| Wu DTY, Chen AT, Manning JD, et al. (2019) Evaluating visual analytics for health informatics applications: a systematic review from the American Medical Informatics Association Visual Analytics Working Group Task Force on Evaluation. Journal of the American Medical Informatics Association : Jamia. 26: 314-323 |