🎉 Congratulations to the relAI PhD student Johanna Topalis and relAI Fellow Prof. Michael Ingrisch!
🏆 The article they co-authored, “ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports”, has been awarded the Most Cited Article in European Radiology (Impact Factor 2024) by the European Society of Radiology! The work was presented at the European Congress of Radiology (ECR) 2026 in Vienna and honoured by the Editor-in-Chief of European Radiology, Prof. Bernd Hamm.
📖 The article presents the first exploratory case study evaluating the quality of simplified radiology reports generated by the large language model (LLM) ChatGPT. Radiologists rated the reports as generally high quality but also identified errors that could lead to harmful patient interpretations. The findings highlight both the potential and the limitations of early large language models in clinical communication: while simplified reports can enhance accessibility, medical expert supervision and domain-specific adaptation are vital to ensure patient safety.
💡 The study, first published as a preprint in December 2022, was among the earliest scientific assessments of ChatGPT's ability to simplify radiology reports for patients. Since then, a rapidly growing body of research has explored the role of large language models in medical text simplification.
👉 Publication: https://link.springer.com/article/10.1007/s00330-023-10213-1
Preprint: https://arxiv.org/abs/2212.14882
