Abstract
Presentation Description :
The advent of multimodal large language models (LLMs) signifies a new era of healthcare diagnostics and decision-making. This work explores the transformative potential of a multi-modal approach for enhanced clinical analysis, leveraging the capabilities of LLMs. By fusing natural language understanding with computer vision, we present a unified framework in LLMs that facilitates comprehensive and interpretable insights into medical images and patient records. By showcasing real-world applications in ophthalmology, we underscore the invaluable contributions of multimodal LLMs to clinical settings. We conclude by addressing future directions and challenges, advocating for responsible AI integration, and the advancement of patient-centric healthcare through multi-modal technology.
This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.