aceLongitudinal symptom severity tracking in vagus nerve stimulation patients: a 2-stage LLM-based pipeline with explainable AI
Objectives To produce the first structured longitudinal dataset of symptom severity trajectories in vagus nerve stimulation (VNS) patients using a 2-stage large language model pipeline for automated symptom severity extraction from clinical notes, as part of the NIH-funded research evaluating vagal excitations and anatomical linkages (U54AT012307). Materials and methods We analyzed 1427 annotated clinical notes from 95 patients across 5 corpora. LLaMA models (3.2-1B, 3.2-3B, and 3.3-70B) were fine-tuned to class…
Fine-tuned LLaMA models extracted symptom presence and severity from free-text notes with high F1 scores, enabling the first structured quarterly trajectories for VNS patients.
Evidence
- Peer-reviewedJAMIA Open2026-10-01
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Truvace Impact Record TRV-2026-1260, v1: “Longitudinal symptom severity tracking in vagus nerve stimulation patients: a 2-stage LLM-based pipeline with explainable AI.” Truvace, 2026-10-03. /record/TRV-2026-1260 (accessed at citation time). sha256 fda06cf647b991e6…
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