Vol. 1 No. 3 (2026)

Articles

Evidence Retrieval in Clinical Guideline Libraries under Semantic Search Filters and Data Governance

Published 2026-05-26

  • Alice Ross

Alice Ross
School of Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

Language, Knowledge and Intelligent Systems, Volume 1, Issue 3, 2026 cover

Abstract

The exponential growth of medical knowledge has positioned clinical guideline libraries as indispensable resources for evidence-based medicine. However, the sheer volume and complexity of available documents present significant challenges for healthcare professionals seeking timely, accurate, and contextually relevant information. This paper provides a comprehensive academic exploration of how evidence retrieval in clinical guideline libraries can be fundamentally improved through the integration of semantic search filters and robust data governance frameworks. Traditional lexical search methodologies often fail to capture the nuanced clinical context, leading to information overload or the omission of critical guidelines. By implementing semantic search filters, information retrieval systems can transcend simple keyword matching to understand the underlying concepts, relationships, and clinical intents within user queries. Furthermore, the efficacy of semantic retrieval is heavily contingent upon the quality, standardization, and structural integrity of the underlying data. Data governance emerges as the foundational mechanism ensuring that clinical libraries maintain high-fidelity metadata, standardized ontological mapping, and stringent quality control. Through a detailed analysis of system architectures, methodological frameworks, and retrieval performance metrics, this study demonstrates that the confluence of semantic technologies and systematic data governance drastically enhances both the precision and recall of evidence retrieval. The findings advocate for a paradigm shift in health information systems, moving away from unstructured repositories toward highly governed, semantically enriched knowledge graphs.

Keywords

Evidence Retrieval, Semantic Search, Data Governance, Clinical Guidelines, Information Architecture

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