References
Scheschenja M, Viniol S, Bastian MB, Wessendorf J, König AM, Mahnken AH. Feasibility of GPT-3 and GPT-4 for in-depth patient education prior to interventional radiological procedures: a comparative analysis. Cardiovasc Intervent Radiol. 2024;47(2):245–50. https://doi.org/10.1007/s00270-023-03563-2.
Campbell WA 4th, Chick JFB, Shin D, Makary MS. Understanding ChatGPT for evidence-based utilization in interventional radiology. Clin Imaging. 2024. https://doi.org/10.1016/j.clinimag.2024.110098.
Sood A, Mansoor N, Memmi C, Lynch M, Lynch J. Generative pretrained transformer-4, an artificial intelligence text predictive model, has a high capability for passing novel written radiology exam questions. Int J Comput Assist Radiol Surg. 2024. https://doi.org/10.1007/s11548-024-03071-9.
Ariyaratne S, Jenko N, Mark Davies A, Iyengar KP, Botchu R. Could ChatGPT pass the UK radiology fellowship examinations? Acad Radiol. 2023. https://doi.org/10.1016/j.acra.2023.11.026.
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Beşler, M.S. GPT-4's Performance on the European Board of Interventional Radiology Sample Questions. Cardiovasc Intervent Radiol (2024). https://doi.org/10.1007/s00270-024-03711-2
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DOI: https://doi.org/10.1007/s00270-024-03711-2