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Related Experiment Video

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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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Towards Transforming Expert-based Content to Evidence-based Content.

Soheil Moosavinasab1, Majid Rastegar-Mojarad1, Hongfang Liu2

  • 1Department of Health Sciences Research, Mayo Clinic, Rochester, MN ; University of Wisconsin-Milwaukee, Milwaukee, WI.

AMIA Joint Summits on Translational Science Proceedings. AMIA Joint Summits on Translational Science
|May 9, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a system to enhance clinician content reliability by retrieving and ranking relevant scientific citations from MEDLINE. Incorporating journal relevance and study design significantly improves citation accuracy.

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Area of Science:

  • Medical Informatics
  • Information Retrieval
  • Scientific Communication

Background:

  • Clinicians' written content often lacks scientific references, impacting reliability.
  • Updating medical information with current research is a significant challenge.

Purpose of the Study:

  • To develop and evaluate a system for retrieving and ranking relevant scientific citations for clinicians' text.
  • To improve the scientific rigor and updatability of clinical content through automated referencing.

Main Methods:

  • Utilized information retrieval and multi-level/weighted ranking algorithms to identify relevant citations from MEDLINE.
  • Applied the system to 4,697 Heart Failure papers, comparing abstract-only versus full-text analysis.
  • Incorporated journal relevance and study design type into the ranking process.

Main Results:

  • The system successfully extracts and ranks relevant citations and content snippets from scientific literature.
  • Ranking incorporating journal relevance and study design improved results by approximately 40% compared to content similarity alone.
  • Full-text analysis yielded higher quality extracted snippets than abstract-only analysis.

Conclusions:

  • The proposed approach effectively enhances the reliability of clinicians' written content by integrating scientific evidence.
  • Automated citation retrieval and ranking systems can significantly aid in keeping clinical information scientifically current.
  • Leveraging full-text data and advanced ranking factors optimizes the extraction of relevant scientific information.