ChatGPT Assisting Diagnosis of Neuro-ophthalmology Diseases Based on Case Reports

Yeganeh Madadi, Mohammad Delsoz, Priscilla A. Lao, Joseph W. Fong, TJ Hollingsworth +2 more
9/5/2023
cs.CYcs.AIcs.CL

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Abstract

Objective: To evaluate the efficiency of large language models (LLMs) such as ChatGPT to assist in diagnosing neuro-ophthalmic diseases based on detailed case descriptions. Methods: We selected 22 different case reports of neuro-ophthalmic diseases from a publicly available online database. These cases included a wide range of chronic and acute diseases that are commonly seen by neuro-ophthalmic sub-specialists. We inserted the text from each case as a new prompt into both ChatGPT v3.5 and ChatGPT Plus v4.0 and asked for the most probable diagnosis. We then presented the exact information to two neuro-ophthalmologists and recorded their diagnoses followed by comparison to responses from both versions of ChatGPT. Results: ChatGPT v3.5, ChatGPT Plus v4.0, and the two neuro-ophthalmologists were correct in 13 (59%), 18 (82%), 19 (86%), and 19 (86%) out of 22 cases, respectively. The agreement between the various diagnostic sources were as follows: ChatGPT v3.5 and ChatGPT Plus v4.0, 13 (59%); ChatGPT v3.5 and the first neuro-ophthalmologist, 12 (55%); ChatGPT v3.5 and the second neuro-ophthalmologist, 12 (55%); ChatGPT Plus v4.0 and the first neuro-ophthalmologist, 17 (77%); ChatGPT Plus v4.0 and the second neuro-ophthalmologist, 16 (73%); and first and second neuro-ophthalmologists 17 (17%). Conclusions: The accuracy of ChatGPT v3.5 and ChatGPT Plus v4.0 in diagnosing patients with neuro-ophthalmic diseases was 59% and 82%, respectively. With further development, ChatGPT Plus v4.0 may have potential to be used in clinical care settings to assist clinicians in providing quick, accurate diagnoses of patients in neuro-ophthalmology. The applicability of using LLMs like ChatGPT in clinical settings that lack access to subspeciality trained neuro-ophthalmologists deserves further research.

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Cite this paper

@article{madadi2023chatgpt,
  title  = {ChatGPT Assisting Diagnosis of Neuro-ophthalmology Diseases Based on Case Reports},
  author = {Yeganeh Madadi and Mohammad Delsoz and Priscilla A. Lao and Joseph W. Fong and TJ Hollingsworth and Malik Y. Kahook and Siamak Yousefi},
  year   = {2023},
  eprint = {2309.12361},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2309.12361v1}
}

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