A Novel Multimodal Large Language Model for Interpreting Image-Based Ophthalmology Case Questions: Comparative Analysis of Multiple-Choice and Open-Ended Response

Claude 3.5 Sonnet showed strong capabilities in interpreting image-based ophthalmology questions across all subspecialties, with consistent performance between different question formats. These findings suggest potential applications in ophthalmology education and board examination preparation; however, validation of its utility in real-world clinical scenarios needs further evaluation.