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Knowledge-Based Query Construction Using the CDSS Knowledge Base for Efficient Evidence Retrieval.

Muhammad Afzal1, Maqbool Hussain2, Taqdir Ali3

  • 1Department of Computer Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu Yongin-si, Gyeonggi-do 446-701, Korea. muhammad.afzal@oslab.khu.ac.kr.

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Summary
This summary is machine-generated.

This study introduces an automated method for constructing complex clinical queries using knowledge bases from clinical decision support systems (CDSS). This approach significantly reduces search results while increasing their relevance for evidence-based medicine.

Keywords:
Arden SyntaxCDSSautomated query constructionknowledge-based queriesmedical logic modules

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Area of Science:

  • Medical Informatics
  • Clinical Decision Support
  • Evidence-Based Medicine

Background:

  • Clinical practice relies on evidence, but retrieving it via complex queries is challenging.
  • Manual or semi-automatic methods for evidence retrieval are time-consuming and inefficient.
  • Knowledge bases (KB) within clinical decision support systems (CDSS) offer contextual information for query construction.

Purpose of the Study:

  • To develop an automated method for constructing knowledge-based complex queries.
  • To leverage CDSS KBs for improved clinical evidence retrieval.
  • To enhance the efficiency and relevance of evidence searches for clinicians.

Main Methods:

  • Designed methods to parse CDSS KB rule structures.
  • Extracted terms by analyzing control structures and logical connectives.
  • Executed automatically constructed queries on PubMed to assess performance.

Main Results:

  • Reduced average retrieved citations from 56,249 to 330.
  • Increased average relevance from 1 to 6 terms.
  • Clinician feedback indicated maximized time efficiency.

Conclusions:

  • Automated knowledge-based query construction significantly improves efficiency and relevance in evidence retrieval.
  • This method is valuable for evidence-based medicine, particularly in automated environments like ambient assisted living.
  • The approach streamlines access to critical clinical information, supporting better healthcare decisions.