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New neuro-symbolic pipeline formalizes clinical trial patient-set semantics

By PulseAugur Editorial · [1 sources] ·

Researchers have developed NS-CoT, a neuro-symbolic pipeline designed to interpret and execute natural-language eligibility criteria for clinical trial site-feasibility patient-count estimation. This system utilizes a large language model to structure criteria, followed by symbolic processing and SQL compilation to generate patient sets and counts. The methodology aims to document how criteria are translated, enabling reviewability and fidelity checks against declared reference definitions, though it does not guarantee improved recruitment or trial outcomes. AI

IMPACT This methodology could improve the accuracy and traceability of patient selection for clinical trials.

RANK_REASON The cluster contains a research paper detailing a new methodology and pipeline for a specific domain. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New neuro-symbolic pipeline formalizes clinical trial patient-set semantics

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The cluster contains a research paper detailing a new methodology and pipeline for a specific domain. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Sohyeon Jeon ·

    Formalizing Patient-Set Semantics for OMOP CDM-Based Clinical Trial Feasibility Assessment:A Neuro-Symbolic Methodology for Traceable Site-Feasibility Patient Counts

    This study examines the interpretation and execution of natural-language eligibility criteria for clinical trial site-feasibility patient-count estimation using the OMOP Common Data Model (CDM). It treats each count as the size of a patient set produced under explicitly declared …

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