Budich, BeatriceGarrison, Laura A.Preim, BernhardMeuschke, MoniqueHansen, ChristianProcter, JamesRenata G. RaidouJönsson, DanielHöllt, Thomas2023-09-192023-09-192023978-3-03868-216-52070-5786https://doi.org/10.2312/vcbm.20231216https://diglib.eg.org:443/handle/10.2312/vcbm20231216Data-driven storytelling has experienced significant growth in recent years to become a common practice in various application areas, including healthcare. Within the realm of medical narratives, characters play a pivotal role in connecting audiences with data and conveying complex medical information in an engaging manner that may influence positive behavioral and lifestyle changes on the part of the viewer. However, the process of designing characters that are both informative and engaging remains a challenge. In this paper, we propose an AI-assisted pipeline for character design in the context of data-driven medical stories. Our iterative pipeline blends design sensibilities with automation to reduce the time and artistic expertise needed to develop characters reflective of the underlying data, even when that data is time-oriented as in a cohort study.Attribution 4.0 International LicenseCCS Concepts: Narrative Visualization -> Character Design; AI Image GenerationNarrative VisualizationCharacter DesignAI Image Generation10.2312/vcbm.2023121687-915 pages