Evaluating ChatGPT's competency in radiation oncology: A comprehensive assessment across clinical scenarios.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Published Date: Nov 19, 2024

Abstract

PURPOSE: Artificial intelligence (AI) and machine learning present an opportunity to enhance clinical decision-making in radiation oncology. This study aims to evaluate the competency of ChatGPT, an AI language model, in interpreting clinical scenarios and assessing its oncology knowledge.

Authors

  • Sherif Ramadan
    Department of Oncology, Division of Radiation Oncology, London Health Sciences Centre and Western University, London, ON, Canada.
  • Adam Mutsaers
    Department of Radiation Oncology, London Health Sciences Centre, London, ON, Canada.
  • Po-Hsuan Cameron Chen
    Google Health, Palo Alto, CA USA.
  • Glenn Bauman
    Department of Oncology, London Health Sciences Centre, University of Western Ontario, London, Canada.
  • Vikram Velker
    Department of Oncology, London Health Sciences Centre, London, ON, Canada.
  • Belal Ahmad
    School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China. Electronic address: ahmadbelal@hust.edu.cn.
  • Andrew J Arifin
    Department of Radiation Oncology, London Health Sciences Centre, London, ON, Canada; Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, USA.
  • Timothy K Nguyen
    Department of Radiation Oncology, London Health Sciences Centre, London, ON, Canada.
  • David Palma
    Department of Radiation Oncology, London Health Sciences Centre, London, ON, Canada.
  • Christopher D Goodman
    Department of Radiation Oncology, London Health Sciences Centre, London, ON, Canada.

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