Longitudinal Spatial-Nonspatial Decision Support for Competing Outcomes in Head and Neck Cancer Therapy

March 1st, 2021 - February 28th, 2026

Categories: Applications, Human Factors, Software, User Groups, Visualization, Visual Analytics, Visual Informatics, Human Computer Interaction (HCI), Machine Learning, Data Science


Cancers that depend on the spatial location of the disease affect all ethnicities, and are diagnosed each year in large numbers in the United States, leading to large, rich repositories of patient data. This project develops a longitudinal decision support tool to assist clinicians in selecting treatments that balance survival and side-effects responses to cancer therapy. The project will lead to better insights into the biological and therapeutic factors related to cancer survival and toxicity, allowing personalization of care at the individual level.

This research is sponsored by the National Institutes of Health: National Cancer Institute, and led by EVL faculty and Computer Science associate professor Liz Marai (PI) and co-PI Xinhua Zhang, along with collaborators Guadalupe Canahuate at University of Iowa, and Dave Fuller at University of Texas, MD Anderson Cancer Center.