AI-based character generation for disease stories

A case study using epidemiological data to highlight preventable risk factors

authored by

Sarah Mittenentzwei, Laura A. Garrison, Beatrice Budich, Kai Lawonn, Alexander Dockhorn, Bernhard Preim, Monique Meuschke

Abstract

Data-driven storytelling has grown significantly, becoming prevalent in various fields, including healthcare. In medical narratives, characters are crucial for engaging audiences, making complex medical information accessible, and potentially influencing positive behavioral and lifestyle changes. However, designing characters that are both educational and relatable to effectively engage audiences is challenging. We propose a GenAI-assisted pipeline for character design in data-driven medical stories, utilizing Stable Diffusion, a deep learning text-to-image model, to transform data into visual character representations. This approach reduces the time and artistic skills required to create characters that reflect the underlying data. As a proof-of-concept, we generated and evaluated two characters in a crowd-sourced case study, assessing their authenticity to the underlying data and consistency over time. In a qualitative evaluation with four experts with knowledge in design and health communication, the characters were discussed regarding their quality and refinement opportunities. The characters effectively conveyed various aspects of the data, such as emotions, age, and body weight. However, generating multiple consistent images of the same character proved to be a significant challenge. This underscores a key issue in using generative AI for character creation: the limited control designers have over the output.

Organisation(s)

Institute of Information Processing

External Organisation(s)

Otto-von-Guericke University Magdeburg
University of Bergen (UiB)
Friedrich Schiller University Jena

Type

Article

Journal

i-com

ISSN

1618-162X

Publication date

18.02.2025

Publication status

E-pub ahead of print

Peer reviewed

Yes

ASJC Scopus subject areas

Social Psychology, Information Systems, Business, Management and Accounting (miscellaneous), Communication, Human-Computer Interaction, Computer Networks and Communications

Sustainable Development Goals

SDG 3 - Good Health and Well-being

Electronic version(s)

https://doi.org/10.1515/icom-2024-0041 (Access: Open)