A multi-stage framework with prompt calibration, rule-based filtering, semantic checks, judge LLM review, and predictive validation enables trustworthy LLM extraction of substance use disorder diagnoses from nearly 920,000 clinical notes, achieving F1 of 0.80 and superior care-engagement prediction.
Mayo clinical text analysis and knowledge extrac- tion system (ctakes): Architecture, component evaluation and applications,
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A Multi-Stage Validation Framework for Trustworthy Large-scale Clinical Information Extraction using Large Language Models
A multi-stage framework with prompt calibration, rule-based filtering, semantic checks, judge LLM review, and predictive validation enables trustworthy LLM extraction of substance use disorder diagnoses from nearly 920,000 clinical notes, achieving F1 of 0.80 and superior care-engagement prediction.