J Neuroophthalmol
October 2024
Background: To evaluate the accuracy of Chat Generative Pre-Trained Transformer (ChatGPT), a large language model (LLM), to assist in diagnosing neuro-ophthalmic diseases based on case reports.
Methods: We selected 22 different case reports of neuro-ophthalmic disorders from a publicly available online database. These cases included a wide range of chronic and acute diseases commonly seen by neuro-ophthalmologists.
Background: This study evaluates the diagnostic performance of several AI models, including Deepseek, in diagnosing corneal diseases, glaucoma, and neuro□ophthalmologic disorders.
Methods: We retrospectively selected 53 case reports from the Department of Ophthalmology and Visual Sciences at the University of Iowa, comprising 20 corneal disease cases, 11 glaucoma cases, and 22 neuro□ophthalmology cases. The case descriptions were input into DeepSeek, ChatGPT□4.
Purpose: To evaluate the efficiency of large language models (LLMs) including ChatGPT to assist in diagnosing neuro-ophthalmic diseases based on case reports.
Design: Prospective study.
Subjects Or Participants: We selected 22 different case reports of neuro-ophthalmic diseases from a publicly available online database.
High-grade B-cell lymphoma (HGBL) with and and/or rearrangements, also known as a double-hit and triple-hit lymphoma, is an aggressive non-Hodgkin lymphoma affecting older adults. After formal recognition of this entity in the 2017 revision of the World Health Organization Classification of lymphoid neoplasms, only two well-documented cases of triple-hit lymphoma of the orbit appear in the literature. Herein, we describe a 70-year-old man with progressive diplopia, ophthalmoplegia, and rapidly enlarging temporal mass.
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