AI RESEARCH
Whole-body CT attenuation and volume charts from routine clinical scans via evidence-grounded LLM report filtering
arXiv CS.CV
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ArXi:2605.05933v1 Announce Type: new Interpreting quantitative CT biomarkers, such as organ volume and tissue attenuation, requires large-scale healthy reference distributions. However, creating these is challenging because clinical datasets are often heavily enriched with pathology. Here, we develop an evidence-grounded, cross-verified large language model (LLM) ensemble to filter pathological findings from radiology reports, enabling the construction of pathology-reduced cohorts from over 350,000 CT examinations.