Skip to main content

Main menu

  • Home
  • Content
    • Current
      • JNMT Supplement
    • Ahead of print
    • Past Issues
    • Continuing Education
    • JNMT Podcast
    • SNMMI Annual Meeting Abstracts
  • Subscriptions
    • Subscribers
    • Rates
    • Journal Claims
    • Institutional and Non-member
  • Authors
    • Submit to JNMT
    • Information for Authors
    • Assignment of Copyright
    • AQARA Requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
    • Corporate & Special Sales
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • SNMMI
    • JNMT
    • JNM
    • SNMMI Journals
    • SNMMI

User menu

  • Subscribe
  • My alerts
  • Log in
  • Log out
  • My Cart

Search

  • Advanced search
Journal of Nuclear Medicine Technology
  • SNMMI
    • JNMT
    • JNM
    • SNMMI Journals
    • SNMMI
  • Subscribe
  • My alerts
  • Log in
  • Log out
  • My Cart
Journal of Nuclear Medicine Technology

Advanced Search

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • Continuing Education
    • JNMT Podcast
    • SNMMI Annual Meeting Abstracts
  • Subscriptions
    • Subscribers
    • Rates
    • Journal Claims
    • Institutional and Non-member
  • Authors
    • Submit to JNMT
    • Information for Authors
    • Assignment of Copyright
    • AQARA Requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
    • Corporate & Special Sales
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • Watch or Listen to JNMT Podcast
  • Visit SNMMI on Facebook
  • Join SNMMI on LinkedIn
  • Follow SNMMI on Twitter
  • Subscribe to JNMT RSS feeds
Research ArticleQuality and Practice Management

ChatGPT and Patient Information in Nuclear Medicine: GPT-3.5 Versus GPT-4

Geoff Currie, Stephanie Robbie and Peter Tually
Journal of Nuclear Medicine Technology September 2023, jnmt.123.266151; DOI: https://doi.org/10.2967/jnmt.123.266151
Geoff Currie
1School of Dentistry and Medical Sciences, Charles Sturt University, Wagga Wagga, New South Wales, Australia;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Stephanie Robbie
2Queensland X-Ray, St. Andrews Hospital, Toowoomba, Queensland, Australia; and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Peter Tually
1School of Dentistry and Medical Sciences, Charles Sturt University, Wagga Wagga, New South Wales, Australia;
3Telemed Health, Kalgoorlie, Western Australia, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Additional Files
  • FIGURE 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 1.

    Mosaic plot of responses from 3 assessors for each GPT-3.5 and GPT-4 evaluation. Colored column widths are proportion of each evaluation category, and corresponding number is absolute number of questions classified for that category.

  • FIGURE 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 2.

    Percentage of responses in each category (accuracy, appropriateness, currency, and fitness for purpose) demonstrating improved outcomes for GPT-4 compared with GPT-3.5.

  • FIGURE 3.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 3.

    Radar plot of accuracy, appropriateness, currency, and fitness-for-purpose criteria for GPT-3.5, GPT-4, and minimum standard expected by assessors.

Tables

  • Figures
  • Additional Files
    • View popup
    TABLE 1.

    Results Across 7 ChatGPT Generated Information Sheets Among 3 Expert Assessors

    GPT-3.5GPT-4
    ParameterPoorBelow averageAverageAbove averagePoorBelow averageAverageAbove average
    Overall accuracy16.3%72.8%10.9%0%4.8%20.4%60.5%14.3%
     Procedure is accurately explained1191031152
     Preparation is accurate9102034113
     Postprocedure requirements are correct1164006123
     Potential side effects or risks are correctly outlined0183005124
     Content is relevant to procedure1173005115
     Information is evidence-based1173005142
     All information is accurate1200014142
    Overall appropriateness0%11.4%88.6%0%5.7%4.8%52.4%37.1%
     Medical terminology is appropriate and explained in layperson’s terms0021001128
     Language and tone are appropriate for target patients and their families0021001128
     Information is presented in clear, organized manner0615003711
     Any cultural or linguistic considerations have been considered0615060141
     Professional tone is used in patient-appropriate way00210001011
    Overall currency21.4%57.1%21.4%0%8.3%26.2%53.6%13.1%
     Content is up to date1191004134
     Information reflects current best practice4170026103
     Information is free from bias0417001173
     There is no key information omitted1380051151
    Is this adequate for purposes of informed consent?1271031143
    • Mode is highlighted in bold. There were no excellent responses.

    • View popup
    TABLE 2.

    Total Responses Across 7 ChatGPT-Generated Information Sheets Among 3 Expert Assessors

    GPT-3.5GPT-4
    Information sheetPoorBelow averageAverageAbove averagePoorBelow averageAverageAbove average
    Bone scan089000710
    Myocardial perfusion386004112
    Thyroid scan0116013130
    Ventilation–perfusion lung scan0116000161
    18F-FDG PET scan296001124
    Captopril renal scan296002123
    89Sr palliation386002132
    Total percentage of responses8.4%53.8%37.8%0%0.8%10.1%70.6%18.5%
    • Mode is highlighted in bold. There were no excellent responses.

Additional Files

  • Figures
  • Tables
  • Supplemental Data

    Files in this Data Supplement:

    • Supplemental Data
PreviousNext
Back to top

In this issue

Journal of Nuclear Medicine Technology: 53 (1)
Journal of Nuclear Medicine Technology
Vol. 53, Issue 1
March 1, 2025
  • Table of Contents
  • About the Cover
  • Index by author
  • Complete Issue (PDF)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Journal of Nuclear Medicine Technology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
ChatGPT and Patient Information in Nuclear Medicine: GPT-3.5 Versus GPT-4
(Your Name) has sent you a message from Journal of Nuclear Medicine Technology
(Your Name) thought you would like to see the Journal of Nuclear Medicine Technology web site.
Citation Tools
ChatGPT and Patient Information in Nuclear Medicine: GPT-3.5 Versus GPT-4
Geoff Currie, Stephanie Robbie, Peter Tually
Journal of Nuclear Medicine Technology Sep 2023, jnmt.123.266151; DOI: 10.2967/jnmt.123.266151

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
ChatGPT and Patient Information in Nuclear Medicine: GPT-3.5 Versus GPT-4
Geoff Currie, Stephanie Robbie, Peter Tually
Journal of Nuclear Medicine Technology Sep 2023, jnmt.123.266151; DOI: 10.2967/jnmt.123.266151
Twitter logo Facebook logo LinkedIn logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Bookmark this article

Jump to section

  • Article
    • Abstract
    • EVALUATING CHATGPT
    • DISCUSSION
    • CONCLUSION
    • DISCLOSURE
    • ACKNOWLEDGMENT
    • Footnotes
    • REFERENCES
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • PDF

Related Articles

  • PubMed
  • Google Scholar

Cited By...

  • Systematic Review of Large Language Models for Patient Care: Current Applications and Challenges
  • A Season of Celebration
  • Google Scholar

More in this TOC Section

  • Technologist-Based Implementation of Total Metabolic Tumor Volume into Clinical Practice
  • Thyroid Uptake Exceeding 100%: Causes and Prevention
Show more Quality and Practice Management

Similar Articles

Keywords

  • GPT-4
  • patient education
  • ChatGPT
  • generative AI
  • language model
SNMMI

© 2025 SNMMI

Powered by HighWire