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Updated: May 19, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Trustworthiness and relevance in web-based clinical question answering
Sarah Cruchet1, Célia Boyer, Lonneke van der Plas
1Health on the Net Foundation, Geneva, Switzerland. sarah.cruchet@healthonnet.org
This study on clinical question answering (QA) systems found that prioritizing trustworthy sources does not harm answer relevance. In fact, using certified websites for clinical QA improved answer relevance and trustworthiness.
Area of Science:
- Medical Informatics
- Natural Language Processing
- Information Retrieval
Background:
- Clinical question answering (QA) systems aim to provide precise and relevant answers to user queries.
- Ensuring the trustworthiness of answers is critical in the clinical domain.
- Limiting document sources to certified websites enhances trustworthiness but may reduce answer relevance.
Purpose of the Study:
- To evaluate the impact of prioritizing trustworthiness on answer relevance in a clinical QA system.
- To determine if limiting document sources to certified websites negatively affects the relevance of retrieved answers.
Main Methods:
- A comparative evaluation of a clinical QA system was conducted.
- The system's document collection was limited to certified websites to enhance trustworthiness.
- Answer relevance and trustworthiness were assessed.
Main Results:
- Promoting trustworthiness by using certified websites did not negatively impact answer relevance.
- The clinical QA system demonstrated improved answer relevance when using trustworthy sources.
- Both trustworthiness and relevance of answers were enhanced.
Conclusions:
- Limiting document sources to certified websites is an effective strategy for clinical QA systems.
- Enhancing trustworthiness in clinical QA does not compromise, and can even improve, answer relevance.
- This approach supports the development of more reliable and effective clinical decision support tools.
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