Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Higher Mental Functions of the Brain: Language01:10

Higher Mental Functions of the Brain: Language

Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same authorSame journal

Characterizing the Role of Ophthalmologists in the Care of Patients With Suspected Giant Cell Arteritis at an Academic Medical Center.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society·2026
Same author

Compressive Optic Neuropathy Due to Dolichoectatic Ophthalmic Artery.

Neuro-ophthalmology (Aeolus Press)·2026
Same author

Glucagon-Like Peptide-1 Receptor Agonists and the Risk of Non-Arteritic Anterior Ischemic Optic Neuropathy: A Consensus Statement by the North American Neuro-Ophthalmology Society and the American Academy of Ophthalmology.

Ophthalmology·2026
Same author

Diagnosis of High Intracranial Pressure by Non-Optic Nerve Retinal Image Features.

Translational vision science & technology·2026
Same author

Optic Atrophy in Wolfram Syndrome Type 1: A Retrospective Analysis of Visual Outcomes and Biomarker Correlates.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society·2026
Same author

Author response to letter.

Journal of the neurological sciences·2026
Same journal

Concurrence of Inherited Nuclear and Mitochondrial DNA Optic Neuropathies.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society·2026
Same journal

Aspergillus-Infiltrated Optic Nerve Sheath Meningioma in Immunocompetent Host Mimicking Optic Neuritis.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society·2026
Same journal

Progression of Vitreous Detachment Leading to Exacerbation of Visual Field Loss in Acute Nonarteritic Anterior Ischemic Optic Neuropathy.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society·2026
Same journal

Optic Disc Drusen Is Frequently Not Reported on Computed Tomography Scans Performed for Other Reasons.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society·2026
Same journal

Dorsal Midbrain Syndrome Due to Complicated Posterior Reversible Encephalopathy Syndrome.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society·2026
See all related articles

Related Experiment Video

Updated: Jun 23, 2026

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.0K

A Comparative Study of Large Language Models, Human Experts, and Expert-Edited Large Language Models to

Prashant D Tailor1, Lauren A Dalvin, Matthew R Starr

  • 1Department of Ophthalmology (PDT, LAD, MRS, DAT, KDC, MCB, SAM, JJC), Mayo Clinic, Rochester, Minnesota; Departments of Ophthalmology (HEM) and Neurology & Neurological Sciences (HEM), Stanford University, Palo Alto, California; Department of Ophthalmology (KEL, MWK, DDM), Glick Eye Institute, Indiana University School of Medicine, Indianapolis, Indiana; Ophthalmology Service (KEL), Richard L. Roudebush Veterans' Administration Medical Center, Indianapolis, Indiana; Department of Ophthalmology and Visual Sciences (KEL), University of Louisville, Louisville, Kentucky; Midwest Eye Institute (KEL), Carmel, Indiana; Circle City Neuro-Ophthalmology (KEL), Carmel, Indiana; Department of Neurology (MWK, DDM), Indiana University, Indianapolis, Indiana; Department of Ophthalmology (MADN, OMD), Mayo Clinic, Scottsdale, Arizona; and Department of Ophthalmology (MLP, ERE), Mayo Clinic, Jacksonville, Florida.

Journal of Neuro-Ophthalmology : the Official Journal of the North American Neuro-Ophthalmology Society
|April 2, 2024
PubMed
Summary
This summary is machine-generated.

Expert-edited large language model (LLM) responses in neuro-ophthalmology achieved higher quality and empathy scores than human experts alone. This suggests LLMs, when refined by experts, offer significant potential for clinical applications.

More Related Videos

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

7.5K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

554

Related Experiment Videos

Last Updated: Jun 23, 2026

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.0K
Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

7.5K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

554

Area of Science:

  • Medical Artificial Intelligence
  • Clinical Informatics
  • Neuro-ophthalmology

Background:

  • Effectiveness of large language models (LLMs) in medicine compared to human experts is not well-established.
  • This study investigates the quality and empathy of responses generated by human experts, LLMs, and expert-augmented LLMs in neuro-ophthalmology.

Purpose of the Study:

  • To compare the quality and empathy of responses from human experts, various large language models (LLMs), and expert-edited LLM outputs.
  • To evaluate the performance of different LLMs (ChatGPT-3.5, ChatGPT-4, Claude 2, Bing, Bard) in a specialized medical field.

Main Methods:

  • A randomized, masked, multicenter cross-sectional study involving 13 neuro-ophthalmology experts.
  • Experts answered 21 neuro-ophthalmology questions and edited ChatGPT-4 responses, with response times recorded.
  • Anonymized responses from Expert + AI, human experts, and 5 LLMs were evaluated by 12 blinded experts on quality and empathy (1-5 scale).

Main Results:

  • Expert + AI responses yielded the highest scores for both quality (4.16 ± 0.81) and empathy (3.63 ± 0.87).
  • Expert-edited LLM responses significantly outperformed human expert responses in quality (P < 0.0001) and empathy (P = 0.002).
  • ChatGPT-4 and ChatGPT-3.5 showed strong performance, while Bard and Bing also demonstrated competitive results.

Conclusions:

  • Expert-edited large language model (LLM) responses demonstrate superior quality and empathy compared to human experts alone.
  • The findings support further investigation into the integration of expert-refined LLMs for enhancing clinical practice in neuro-ophthalmology.