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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

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Bat-Inspired Algorithm Based Query Expansion for Medical Web Information Retrieval.

Ilyes Khennak¹, Habiba Drias²

¹Laboratory for Research in Artificial Intelligence, Computer Science Department, USTHB, BP 32 El Alia 16111, Bab Ezzouar, Algiers, Algeria. ikhennak@usthb.dz.

Journal of Medical Systems

|January 6, 2017

Summary

This summary is machine-generated.

This study introduces a Bat Algorithm for medical query expansion, improving search result accuracy for health information seekers. The method efficiently identifies optimal expanded queries, enhancing information retrieval from medical databases.

Keywords:

Bat algorithm MEDLINE Medical data management Query expansion Retrieval feedback Swarm intelligence Web intelligence

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Area of Science:

Medical Informatics
Artificial Intelligence
Information Retrieval

Background:

Growing volume of online medical data necessitates effective information retrieval.
Laypeople often struggle with imprecise search queries due to limited medical knowledge.
Existing search engines fail to provide accurate results for vague medical queries.

Purpose of the Study:

To enhance the effectiveness of query expansion in the medical domain.
To propose an original approach using the Bat Algorithm for optimizing medical search queries.
To address the challenge of imprecise user queries in accessing online health information.

Main Methods:

An novel approach utilizing the Bat Algorithm for query expansion in the medical field.
The Bat Algorithm is employed to select the optimal expanded query from candidate sets.
Empirical determination of the expanded query length is incorporated.

Main Results:

The proposed Bat Algorithm-based approach demonstrates improved retrieval effectiveness.
The method achieves higher efficiency compared to baseline approaches.
Numerical results on the MEDLINE database validate the approach's performance.

Conclusions:

The Bat Algorithm offers an effective and efficient solution for medical query expansion.
This approach improves the accuracy and relevance of search results for health information.
The method successfully overcomes limitations of imprecise user queries in medical information retrieval.