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Can DALL-E 3 Reliably Generate 12-Lead ECGs and Teaching Illustrations?
Zhu, Lingxuan; Mou, Weiming; Wu, Keren; Zhang, Jian; Luo, Peng.
Afiliación
  • Zhu L; Department of Oncology, Zhujiang Hospital of Southern Medical University, Guangzhou, CHN.
  • Mou W; Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, CHN.
  • Wu K; Department of Oncology, Zhujiang Hospital of Southern Medical University, Guangzhou, CHN.
  • Zhang J; Department of Oncology, Zhujiang Hospital of Southern Medical University, Guangzhou, CHN.
  • Luo P; Department of Oncology, Zhujiang Hospital of Southern Medical University, Guangzhou, CHN.
Cureus ; 16(1): e52748, 2024 Jan.
Article en En | MEDLINE | ID: mdl-38384621
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.
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Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Cureus Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Cureus Año: 2024 Tipo del documento: Article