Integration of AI-Generated Images in Clinical Otolaryngology

Abstract

Recent advances in generative artificial intelligence (AI) have enabled remarkable capabilities in generating images, audio, and videos from textual descriptions. Tools like <i>Midjourney</i> and <i>DALL-E 3</i> can produce striking visualizations from simple prompts, while services like <i>Kaiber.ai</i> and <i>RunwayML Gen-2</i> can generate short video clips. These technologies offer intriguing possibilities for clinical and educational applications in otolaryngology. Visualizing symptoms like vertigo or tinnitus could bolster patient-provider understanding, especially for those with communication challenges. One can envision patients selecting images to complement chief complaints, with AI-generated differential diagnoses. However, inaccuracies and biases necessitate caution. Images must serve to enrich, not replace, clinical judgment. While not a substitute for healthcare professionals, text-to-image and text-to-video generation could become valuable complementary diagnostic tools. Harnessed judiciously, generative AI offers new ways to enhance clinical dialogues. However, education on proper, equitable usage is paramount as these rapidly evolving technologies make their way into medicine.

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