Jul 2026· Journal of imaging informatics in medicine· 0 citations· 15 references
Medicine
TL;DR
Dual-reader oversight significantly improves the safety and reliability of LLM-based communication tools and quantified the incremental benefit of multi-reader oversight in detecting errors in patient-facing LLM responses.
Structured prompting improves detection of interpretation and section-consistency errors across seven models and consistently enhances LLM-based error detection, closing the gap between open-source and commercial models and offering a pathway for privacy-preserving, on-premises QA.
Jia Li, Zi-Chun Zhou, Yan-Tao Niu et al.· European Radiology Experimen...· 0 citations
It is suggested that domain-specific training matters more than model scale for PET/CT report error detection, supporting compact models as an accurate and computationally efficient approach to automated radiology report quality assurance.
Hermione Warr, Harry Anthony, Lilli J. Freischem et al.· 0 citations
Successful reader-LLM collaboration is associated with model confidence and reader expertise, with rationale quality facilitating correct advice uptake but increasing overreliance on incorrect suggestions.
Jiyoung Song, Won Gi Jeong, D. Han et al.· Radiology· 2 citations
Large language models can effectively improve the readability of radiology reports, yet all such models inherently suffer from output instability and information omission, so optimized structured prompts can substantially reduce the variability of model outputs and improve the accuracy of medical text translation.
Yun Mao, Chunyan Wang, Wei Wang et al.· Academic Radiology· 0 citations
This paper quantifies the sensitivity of established evaluation metrics to variations in reporting practices and introduces a radiologist-informed taxonomy of variations in radiology reporting practice and a method (ReRef) that rewrites reference reports along the axes of the authors' taxonomy while preserving clinical...
Daniel P. Jeong, Charles Q. Li, H. Hosseiny et al.· 0 citations
We developed a national questionnaire to assess radiology reports (RR) physicians’ reading habits and identify their expectations towards RR, focusing on CT and MRI reports. An anonymized 20-item questionnaire was nationally distributed in France via practice and hospital mailing lists and one social media group, and i...
Yasmine Kassab, Matthieu Bailly, Sixtine Brabant et al.· Insights into Imaging· 0 citations
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