Evaluating the performance of Generative Pre-trained Transformer-4 (GPT-4) in standardizing radiology reports.

Journal: European radiology
Published Date: Nov 8, 2023

Abstract

OBJECTIVE: Radiology reporting is an essential component of clinical diagnosis and decision-making. With the advent of advanced artificial intelligence (AI) models like GPT-4 (Generative Pre-trained Transformer 4), there is growing interest in evaluating their potential for optimizing or generating radiology reports. This study aimed to compare the quality and content of radiologist-generated and GPT-4 AI-generated radiology reports.

Authors

  • Amir M Hasani
    Laboratory of Translation Research, National Heart Blood Lung Institute, NIH, Bethesda, MD, USA.
  • Shiva Singh
    Radiology & Imaging Sciences Department, Clinical Center, NIH, Bethesda, MD, USA.
  • Aryan Zahergivar
    Radiology & Imaging Sciences Department, Clinical Center, NIH, Bethesda, MD, USA.
  • Beth Ryan
    Urology Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
  • Daniel Nethala
    Urology Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
  • Gabriela Bravomontenegro
    Urology Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
  • Neil Mendhiratta
    Urology Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
  • Mark Ball
    Urology Oncology Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
  • Faraz Farhadi
    Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD.
  • Ashkan Malayeri
    Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, USA.

Keywords

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