Can DALL-E 3 Reliably Generate 12-Lead ECGs and Teaching Illustrations?
Lingxuan Zhu, Weiming Mou, Keren Wu, Jian Zhang, Peng Luo
Abstract
The recent integration of the latest image generation model DALL-E 3 into ChatGPT allows text prompts to easily generate the corresponding images, enabling multimodal output from ChatGPT. We explored the feasibility of DALL-E 3 for drawing a 12-lead ECG and found that it can draw rudimentary 12-lead electrocardiograms (ECG) displaying some of the parameters, although the details are not completely accurate. We also explored DALL-E 3's capacity to create vivid illustrations for teaching resuscitation-related medical knowledge. DALL-E 3 produced accurate CPR illustrations emphasizing proper hand placement and technique. For ECG principles, it produced creative heart-shaped waveforms tying ECGs to the heart. With further training, DALL-E 3 shows promise to expand easy-to-understand visual medical teaching materials and ECG simulations for different disease states. In conclusion, DALL-E 3 has the potential to generate realistic 12-lead ECGs and teaching schematics, but expert validation is still needed.