Can Large Language Models Reliably Extract Physiology Index Values from Coronary Angiography Reports?
Coronary angiography (CAG) reports contain clinically relevant physiological measurements, yet this information is typically in the form of unstructured natural language, limiting its use in research. We investigate the use of Large Language Models (LLMs) to automatically extract these values, along with their anatomical locations, from Portuguese CAG reports. To our knowledge, this study is the first addressing physiology indexes extraction from a large (1342 reports) corpus of CAG reports, and one of the few focusing on CAG or Portuguese clinical text. We explore local privacy-preserving general-purpose and medical LLMs under different settings. Prompting strategies included zero-shot, ...
| Authors | Sofia Morgado, Filipa Valdeira, Niklas Sander et al. |
|---|---|
| Primary category | cs.CL |
| Published | 21 March 2026 |
| Last updated at source | 21 March 2026 |
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