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EMNLP 2025mainmain

HealthCards: Exploring Text-to-Image Generation as Visual Aids for Healthcare Knowledge Democratizing and Education

Qian Wu, Zheyao Gao, Longfei Gou, Yifan Hou, Ann Sin Nga Lau, Qi Dou

Chinese University of Hong Kong · Department of Computer Science, Swiss Federal Institute of Technology · The Chinese University of Hong Kong and The Chinese University of Hong Kong · The Chinese University of Hong Kong

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.18653/v1/2025.emnlp-main.1401 ↗

摘要

The evolution of text-to-image (T2I) generation techniques has introduced new capabilities for information visualization, with the potential to advance knowledge democratization and education. In this paper, we investigate how T2I models can be adapted to generate educational health knowledge contents, exploring their potential to make healthcare information more visually accessible and engaging. We explore methods to harness recent T2I models for generating health knowledge flashcards—visual educational aids that present healthcare information through appealing and concise imagery. To support this goal, we curated a diverse, high-quality healthcare knowledge flashcard dataset containing 2,034 samples sourced from credible medical resources. We further validate the effectiveness of fine-tuning open-source models with our dataset, demonstrating their promise as specialized health flashcard generators. Our code and dataset are available at: https://github.com/med-air/HealthCards.