Can Large Language Models Reliably Extract Physiology Index Values from Coronary Angiography Reports?
Sofia Morgado; Filipa Valdeira; Niklas Sander; Diogo Ferreira; Marta Vilela; Miguel Menezes; Cláudia Soares · 2026 · arXiv
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Abstract (excerpt)
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 gen
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Metadata source: arXiv