Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Higher Mental Functions of the Brain: Language

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 author

Fructose-Induced bioenergetic surplus Unlocks fatty acid biosynthesis pathway dominance over reverse β-Oxidation: Mechanistic insights into High-Caproate production from food waste.

Bioresource technology·2026

Same author

Disseminated Histoplasmosis in a Patient With Acquired Immunodeficiency Syndrome: A Case Report and Literature Review.

Cureus·2026

Same author

Atrial fibrillation and cardiovascular comorbidity burden as predictors of in-hospital mortality in acute pancreatitis: A National Inpatient Sample analysis of 1.9 million hospitalizations.

International journal of cardiology. Cardiovascular risk and prevention·2026

Same author

Sub-Zero: A Review of the Current Evidence and Evolving Technologies Enabling Zero‑Fluoroscopy Procedures.

Pacing and clinical electrophysiology : PACE·2026

Same author

Molecular-level analysis of chemical transformation of algal extracellular organic matter during seawater ozonation: Dominant reaction pathways and impacts of halide ions.

Water research·2026

Same author

Exogenous quorum sensing signal enhances central energy metabolism to fuel biofilm formation and denitrification on microplastics.

Journal of hazardous materials·2026

Search research articles

Related Experiment Video

Updated: Jun 29, 2026

Basics of Multivariate Analysis in Neuroimaging Data

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

A Comparative Evaluation of Large Language Model Utility in Neuroimaging Clinical Decision Support.

Luke Miller¹, Peter Kamel², Jigar Patel³

¹Department of Radiology, University of Maryland Medical Center, Baltimore, MD, USA. Luke.Miller@umm.edu.

Journal of Imaging Informatics in Medicine

|November 7, 2024

Summary

Large language models (LLMs) were evaluated for their ability to provide optimal neuroradiology imaging recommendations. GPT-4 and ChatGPT demonstrated superior performance compared to other models like Bard and Llama 2.

Keywords:

Bard ChatGPT GPT4 Imaging utilization LLM

More Related Videos

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Published on: August 12, 2019

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

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

Published on: December 6, 2024

Related Experiment Videos

Last Updated: Jun 29, 2026

Basics of Multivariate Analysis in Neuroimaging Data

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Published on: August 12, 2019

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

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

Published on: December 6, 2024

Area of Science:

Medical Imaging
Artificial Intelligence
Radiology

Background:

Increasing imaging utilization raises concerns about appropriateness in clinical scenarios.
Large language models (LLMs) offer potential as accessible resources for healthcare providers.
The performance of LLMs in generating medical imaging recommendations is understudied.

Purpose of the Study:

To evaluate and compare the appropriateness and usefulness of imaging recommendations from eight LLMs.
To assess LLM performance in response to common neuroradiology clinical scenarios.
To identify the most effective LLMs for guiding optimal medical image ordering.

Main Methods:

Twenty-four neuroradiology clinical scenarios were used to query eight LLMs (ChatGPT, GPT-4, Bard v1/v2, Bing Chat, Llama 2, Perplexity, Claude).
Queries assessed LLM ability to provide accurate, actionable advice on optimal image ordering.
Recommendations were graded by neuroradiologists against ACR Appropriateness Criteria and New Orleans Head CT Criteria.

Main Results:

GPT-4 achieved the highest appropriateness rate (23/24), followed by ChatGPT (20/24), Perplexity (19/24), and Claude (19/24).
Llama 2 (5/24) and Bard v1 (13/24) showed lower appropriateness rates.
GPT-4 and ChatGPT generally outperformed Bard, Bing Chat, and Llama 2 in providing optimal recommendations.

Conclusions:

LLMs show variable performance in providing appropriate neuroradiology imaging recommendations.
GPT-4 and ChatGPT are promising tools for assisting with medical imaging decisions.
Further research is needed to refine LLMs for clinical decision support in radiology.