Diagnostic interpretation of corneal tomography using a multimodal large language model (ChatGPT)

In this proof-of-concept study, a commercially available multimodal LLM was able to extract data from raw corneal tomography reports with high accuracy and with retention of spatial context, and formulated correct diagnoses with excellent proficiency. This study demonstrates the use of emerging LLMs as diagnostic adjuncts through the synthesis of multimodal data.