Ran Score: a LLM-based Evaluation Score for Radiology Report Generation
arXiv:2608.08046v1 Announce Type: new Abstract: Text-conditioned chest X-ray generation aims to synthesize realistic radiographs that faithfully depict specified findings.
arXiv:2605.08445v1 Announce Type: new Abstract: AI models are increasingly deployed in live clinical environments where they must perform reliably across complex, high-stakes
arXiv:2603.17765v1 Announce Type: cross Abstract: Automated radiology report generation has gained increasing attention with the rise of deep learning and large language models.
arXiv:2605.11398v1 Announce Type: new Abstract: We introduce AcuityBench, a benchmark for evaluating whether language models identify the appropriate urgency of care from user
arXiv:2604.16175v1 Announce Type: new Abstract: Automated 3D radiology report generation often suffers from clinical hallucinations and a lack of the iterative verification found
arXiv:2605.13046v1 Announce Type: new Abstract: Mental health disorders affect millions worldwide, and healthcare systems are increasingly overwhelmed by the volume of clinical
arXiv:2605.00421v2 Announce Type: cross Abstract: Large language models (LLMs) show promise in radiology but their deployment is limited by computational requirements that
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