Whole body CT attenuation and volume charts from routine clinical scans via LLM report filtering.

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 (large language model) ensemble to filter pathological findings from radiology reports, enabling the construction of pathology-reduced cohorts from over 350,000 CT examinations.