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Visualizing Symptom Development During Head and Neck Cancer Treatment
Authors: Floricel, C., Wentzel, A., Kumar, N., Nipu, N., Canahuate, G., Dijk, L.V., Marai, G.E.
Publication: IEEE VIS 2020 Poster URL: https://vis2020-ieee.ipostersessions.com/default.aspx?s=22-AA-8D-DC-19-58-EB-1F-C1-70-17-4B-15-2E-08-23 Approximately 100,000 cases of Head and Neck Cancer (HNC) are diagnosed in the US annually. Patients are increasingly likely to survive but often experience acute and long-term side effects. Hence, great importance has been placed by clinicians on improved patient’ quality of life (QoL) and reducing symptom burden during treatment. We introduce an interactive system which enables clinical and computational experts to visualize and assess medical data. However, HNC patient cohort data are ofter large, multi-variate, and incomplete. Also, anatomical and dynamic temporal components influence the outcome of therapy, and the resulting patients’ QoL. Using novel combinations of visual encodings, our system could help clinicians to create better treatment plans. Date: October 25, 2020 - October 30, 2020 Document: View PDF |
