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Updated: Sep 9, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Comparative Analysis of LLMs' Performance On a Practice Radiography Certification Exam.

Kevin R Clark

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    |August 29, 2025
    PubMed
    Summary
    This summary is machine-generated.

    ChatGPT demonstrated the highest accuracy on a practice radiography exam among five large language models (LLMs). While advanced, users must verify AI-generated answers for accuracy due to potential errors.

    Keywords:
    ChatGPTgenerative artificial intelligencepractice certification examradiographylarge language models

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    Area of Science:

    • Artificial Intelligence in Medical Education
    • Radiography Certification Examination
    • Natural Language Processing

    Background:

    • The increasing integration of artificial intelligence (AI) and large language models (LLMs) into various professional fields necessitates an evaluation of their performance in specialized domains.
    • Assessing the capabilities of LLMs in medical education, particularly for high-stakes certification exams, is crucial for understanding their potential and limitations.

    Purpose of the Study:

    • To compare the performance of five leading large language models (LLMs) on a practice radiography certification examination.
    • To identify which LLM exhibits the highest accuracy and to analyze performance across different content categories.

    Main Methods:

    • An exploratory, nonexperimental study was conducted using 200 multiple-choice questions from a practice radiography certification exam.
    • Five LLMs—ChatGPT, Claude, Copilot, Gemini, and Perplexity—were evaluated based on their accuracy in answering these questions.
    • Statistical analysis, including McNemar tests, was employed to determine significant differences in accuracy rates, with performance also broken down by content categories and subcategories.

    Main Results:

    • ChatGPT achieved the highest overall accuracy at 83.5%, outperforming Claude and Gemini significantly.
    • ChatGPT excelled in patient care questions, answering all correctly, and showed strong performance in safety and procedures.
    • Copilot demonstrated the highest accuracy in image production, while ChatGPT led in four out of eight subcategories.

    Conclusions:

    • ChatGPT was the most accurate large language model for the assessed practice radiography certification exam questions.
    • Despite superior performance, users must exercise caution with generative AI, verifying all responses for accuracy due to the potential for generating incorrect information.
    • Future research should explore LLM performance on certification exams in other medical imaging modalities like MRI, nuclear medicine, radiation therapy, and sonography.