Practical Evaluation of ChatGPT Performance for Radiology Report Generation.

Journal: Academic radiology
Published Date: Aug 13, 2024

Abstract

RATIONALE AND OBJECTIVES: The process of generating radiology reports is often time-consuming and labor-intensive, prone to incompleteness, heterogeneity, and errors. By employing natural language processing (NLP)-based techniques, this study explores the potential for enhancing the efficiency of radiology report generation through the remarkable capabilities of ChatGPT (Generative Pre-training Transformer), a prominent large language model (LLM).

Authors

  • Mohsen Soleimani
  • Navisa Seyyedi
    Department of Health Information Management and Medical Informatics, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran. Electronic address: n-seyyedi@razi.tums.ac.ir.
  • Seyed Mohammad Ayyoubzadeh
    Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
  • Sharareh Rostam Niakan Kalhori
    Health Information Management and Medical Informatics Department, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
  • Hamidreza Keshavarz
    Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran.

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