Journal article
Assessment of Differential Diagnoses for Oculoplastics Cases Produced by Large Language Models
Ophthalmic plastic and reconstructive surgery, Vol.42(1), pp.51-57
01/2026
DOI: 10.1097/IOP.0000000000002984
PMID: 40788674
Abstract
This study aimed to evaluate the accuracy of different large language models (LLMs) in generating differential diagnoses for oculoplastic cases.
Differential diagnoses were generated for 20 oculoplastic cases sourced from University of Iowa EyeRounds.org using 6 LLMs: Chat Generative Pre-Trained Transformer (ChatGPT) 3.5, ChatGPT 4.0, OcuSmart/EyeGPT, Google Gemini 1.5, Claude 3.5, and Microsoft CoPilot. Outputs were compared against the EyeRounds expert-curated differentials examining (1) top diagnosis match rate (2) inclusion of the correct diagnosis within the generated list, as well as (3) recall and (4) precision, calculated to assess the overlap and conciseness of LLM outputs.
OcuSmart/EyeGPT achieved the highest top diagnosis match rate (85 ± 36%), while Claude 3.5 demonstrated the highest rate of inclusion of correct diagnosis in differential, as well as recall rate (100 ± 0% and 55 ± 27%, respectively). Google Gemini produced the most precise differentials at 43 ± 24%. Claude 3.5 generated the largest but least concise lists. LLM performance varied by case; for example, idiopathic orbital inflammation cases yielded highest recall and top diagnosis match across all models, while floppy eyelid syndrome cases demonstrated lowest performance.
LLMs show promising potential in diagnosing oculoplastic cases, with OcuSmart/EyeGPT and Claude 3.5 performing best for determining the case diagnosis and recall, and ChatGPT 3.5, OcuSmart/EyeGPT, and Gemini generating concise and relevant differentials. However, further research and development are necessary to validate LLMs' capabilities and integrate them into the clinical workflow.
Details
- Title: Subtitle
- Assessment of Differential Diagnoses for Oculoplastics Cases Produced by Large Language Models
- Creators
- Jeffrey C Peterson - University of Illinois ChicagoSruti S Rachapudi - University of Illinois ChicagoSasha Hubschman - University of Illinois ChicagoKevin Heinze - Lander InstituteThomas Oetting - University of IowaSean M Rodriguez - University of IowaPete Setabutr - University of Illinois Urbana-ChampaignAnn Q Tran - University of Illinois Urbana-Champaign
- Resource Type
- Journal article
- Publication Details
- Ophthalmic plastic and reconstructive surgery, Vol.42(1), pp.51-57
- DOI
- 10.1097/IOP.0000000000002984
- PMID
- 40788674
- NLM abbreviation
- Ophthalmic Plast Reconstr Surg
- ISSN
- 0740-9303
- eISSN
- 1537-2677
- Publisher
- LIPPINCOTT WILLIAMS & WILKINS; PHILADELPHIA
- Language
- English
- Electronic publication date
- 08/11/2025
- Date published
- 01/2026
- Academic Unit
- Ophthalmology and Visual Sciences
- Record Identifier
- 9984946610502771
Metrics
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