ArticleBMC emergency medicine2026
RapidNeuroGuide: an NLP-enhanced AI platform for digital headache triage and clinical decision support.
Article in BMC emergency medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundHeadache is among the most frequent presenting complaints in emergency departments worldwide, yet differentiating life-threatening secondary causes from benign primary headaches remains a persistent clinical challenge.
objectiveThis study describes Phase I of the RapidNeuroGuide development roadmap, comprising the development and an initial literature-derived technical proof-of-concept evaluation of a three-layer AI-driven headache triage engine that integrates critical threshold detection, SNNOOP10 red-flag scoring, and expert-weighted risk assessment.
methodsA total of 240 PubMed-indexed headache articles were screened, and 121 full-text documents were acquired from legally accessible sources. The S-PubMedBERT-MS-MARCO sentence-transformer model was used to identify clinically relevant sentences, which were mapped to 23 structured clinical fields using a deterministic terminology dictionary comprising 103 expressions. The resulting 158 curated, literature-derived case representations constituted the proof-of-concept evaluation dataset.
resultsExact agreement with the predefined reference triage classification was observed in 110 of 158 case representations (69.6%), while 157 cases (99.4%) were assigned within one adjacent triage category. One case (0.6%) differed by more than one category. All 47 case representations carrying a predefined CRITICAL reference classification were assigned to the CRITICAL category within the evaluated dataset. The NLP pipeline produced usable structured parameter sets for 114 of 119 machine-readable documents (95.8%), with a mean cosine similarity of 0.878 across 570 retained sentences.
conclusionsRapidNeuroGuide demonstrated preliminary technical feasibility and measurable agreement with predefined reference triage categories in this Phase I proof-of-concept evaluation.
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