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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
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PubMedReco: A Real-Time Recommender System for PubMed Citations.

Hamman W Samuel1, Osmar R Zaïane1

  • 1Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada.

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|January 4, 2018
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PubMedReco offers real-time medical article recommendations from PubMed directly within chat environments. This system enhances user experience by automatically searching and displaying relevant citations, improving access to medical literature.

Keywords:
Information Storage and RetrievalMedical Informatics ApplicationsPubMed

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Area of Science:

  • Medical Informatics
  • Computer Science

Background:

  • Accessing medical literature from PubMed typically requires users to leave their current communication interface.
  • Searching for relevant medical articles can be time-consuming and disruptive in synchronous environments.

Purpose of the Study:

  • To develop and evaluate PubMedReco, a recommender system for real-time medical article suggestions.
  • To improve the user experience of searching PubMed within health forums and chat rooms.

Main Methods:

  • PubMedReco analyzes conversation keywords to automatically generate PubMed search queries.
  • It utilizes the PubMed E-utilities programming interface to retrieve relevant citations.
  • A machine learning model is employed for identifying relevant keywords from conversations.

Main Results:

  • PubMedReco successfully integrates PubMed article recommendations into a chat interface.
  • The system demonstrates feasibility in providing real-time, relevant medical literature suggestions.
  • User experience is enhanced by eliminating the need to manually search PubMed.

Conclusions:

  • PubMedReco offers a novel solution for seamless access to medical information during online health discussions.
  • The system has the potential to improve knowledge sharing and evidence-based practice in digital health communities.