Evaluating the clinical utility of multimodal large language models in rare maculopathy.

ABSTRACT: This study aimed to assess how multimodal large language models (MLLM) diagnose and differentiate Pentosan Polysulfate (PPS) Maculopathy from other phenotypic mimics. A retrospective review of clinical records and multimodal retinal imaging was conducted with patients from the Shiley Eye Institute and Casey Eye Institute. Four MLLMs (ChatGPT-4o, Claude 3.5 Sonnet, Google Gemini 1.5 Pro, Perplexity Llama 3.1 Sonar/Default) along with human retinal specialists answered prompts based on retinal imaging and demographic data. Performance was evaluated using accuracy, sensitivity and specificity estimates. The study included 126 eyes from 63 patients, with 36 eyes with PPS maculopathy, 50 eyes with Stargardt disease, and 40 eyes with PRPH2-associated multifocal pattern dystrophy. MLLMs showed im

SUBMITTER: Tran MD 

PROVIDER: S-EPMC12764543 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature