Hi ChatGPT, I am a Radiologist, How can you help me?

Journal: La Radiologia medica
Published Date:

Abstract

This review paper explores the integration of ChatGPT, a generative AI model developed by OpenAI, into radiological practices, focusing on its potential to enhance the operational efficiency of radiologists. ChatGPT operates on the GPT architecture, utilizing advanced machine learning techniques, including unsupervised pre-training and reinforcement learning, to generate human-like text responses. While AI applications in radiology predominantly focus on imaging acquisition, reconstruction, and interpretation-commonly embedded directly within hardware-the accessibility and functional breadth of ChatGPT make it a unique tool. This interview-based review should not be intended as a detailed evaluation of all ChatGPT features. Instead, it aims to test its utility in everyday radiological tasks through real-world examples. ChatGPT demonstrated strong capabilities in structuring radiology reports according to international guidelines (e.g., PI-RADS, CT reporting for diverticulitis), designing a complete research protocol, and performing advanced statistical analysis from Excel datasets, including ROC curve generation and intergroup comparison. Although not capable of directly interpreting DICOM images, ChatGPT provided meaningful assistance in image post-processing and interpretation when images were converted to standard formats. These findings highlight its current strengths and limitations as a supportive tool for radiologists.

Authors

  • Davide Bellini
    Academic Diagnostic Imaging Division - I.C.O.T. Hospital, Department of Medical-Surgical Sciences and Biotechnologies, Faculty of Pharmacy and Medicine, University of Rome "Sapienza", Via F. Faggiana 1668, 04100, Latina, Italy. bellinidavide29@gmail.com.
  • Riccardo Ferrari
    Department of Urology, Azienda Ospedaliero-Universitaria di Modena, Italy.
  • Simone Vicini
    Academic Diagnostic Imaging Division - I.C.O.T. Hospital, Department of Medical-Surgical Sciences and Biotechnologies, Faculty of Pharmacy and Medicine, University of Rome "Sapienza", Via F. Faggiana 1668, 04100, Latina, Italy.
  • Marco Rengo
    Department of Radiological Sciences, Oncology and Pathology, University La Sapienza, AOU Sant'Andrea, Via di Grottarossa 1035, 00189 Rome, Italy.
  • Carlos Leon Saletti
    Academic Diagnostic Imaging Division - I.C.O.T. Hospital, Department of Medical-Surgical Sciences and Biotechnologies, Faculty of Pharmacy and Medicine, University of Rome "Sapienza", Via F. Faggiana 1668, 04100, Latina, Italy.
  • Iacopo Carbone
    Academic Diagnostic Imaging Division - I.C.O.T. Hospital, Department of Medical-Surgical Sciences and Biotechnologies, Faculty of Pharmacy and Medicine, University of Rome "Sapienza", Via F. Faggiana 1668, 04100, Latina, Italy.

Keywords

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