Conference proceeding
A Tale of Two Centers: Visual Exploration of Health Disparities in Cancer Care
2022 IEEE 15th Pacific Visualization Symposium (PacificVis), pp.101-110
04/2022
DOI: 10.1109/PacificVis53943.2022.00019
Abstract
The annual incidence of head and neck cancers (HNC) worldwide is more than 550,000 cases, with around 300,000 deaths each year. However, the incidence rates and disease-characteristics of HNC differ between treatment centers and different populations, due to undetermined reasons, which may or not include socioeconomic factors. The multi-faceted and multi-variate nature of the data in the context of the emerging field of health disparities research makes automated analysis impractical. Hence, we present a visual analysis approach to explore the health disparities in the data of HNC patients from two different cohorts at two cancer care centers. Our approach integrates data from multiple sources, including census data and city data, with custom visual encodings and with a nearest neighbor approach. Our design, created in collaboration with oncology experts, makes it possible to analyze the patients' demographic, disease characteristics, treatments and outcomes, and to make significant comparisons of these two cohorts and of individual patients. We evaluate this approach through two case studies performed with domain experts. The results demonstrate that this visual analysis approach successfully accomplishes the goal of comparing two cohorts in terms of different significant factors, and can provide insights into the main source of health disparities between the two centers.
Details
- Title: Subtitle
- A Tale of Two Centers: Visual Exploration of Health Disparities in Cancer Care
- Creators
- Sanjana Srabanti - University of Illinois ChicagoMichael Tran - University of Illinois ChicagoVirginie Achim - University of Illinois ChicagoDavid Fuller - University of TexasGuadalupe Canahuate - University of IowaFabio Miranda - University of Illinois ChicagoG.Elisabeta Marai - University of Illinois Chicago
- Resource Type
- Conference proceeding
- Publication Details
- 2022 IEEE 15th Pacific Visualization Symposium (PacificVis), pp.101-110
- DOI
- 10.1109/PacificVis53943.2022.00019
- eISSN
- 2165-8773
- Publisher
- IEEE
- Grant note
- NSF-CNS-1828265,NSF-CDSE-1854815 / US National Science Foundation (10.13039/100000001) NIH-LM-012527,NIH-NCI-CA258827 / US National Institutes of Health (10.13039/100000002)
- Language
- English
- Date published
- 04/2022
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984267160002771
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