ArXiv Preprint
The release of ChatGPT, a language model capable of generating text that
appears human-like and authentic, has gained significant attention beyond the
research community. We expect that the convincing performance of ChatGPT
incentivizes users to apply it to a variety of downstream tasks, including
prompting the model to simplify their own medical reports. To investigate this
phenomenon, we conducted an exploratory case study. In a questionnaire, we
asked 15 radiologists to assess the quality of radiology reports simplified by
ChatGPT. Most radiologists agreed that the simplified reports were factually
correct, complete, and not potentially harmful to the patient. Nevertheless,
instances of incorrect statements, missed key medical findings, and potentially
harmful passages were reported. While further studies are needed, the initial
insights of this study indicate a great potential in using large language
models like ChatGPT to improve patient-centered care in radiology and other
medical domains.
Katharina Jeblick, Balthasar Schachtner, Jakob Dexl, Andreas Mittermeier, Anna Theresa Stüber, Johanna Topalis, Tobias Weber, Philipp Wesp, Bastian Sabel, Jens Ricke, Michael Ingrisch
2022-12-30
