SBRS: Bridging the Gap between Biomedical Research and Clinical Practice

  • Santiago Timón-Reina
  • Rafael Martínez-Tomás
  • Mariano Rincón-Zamorano
  • Tomás García-Sáiz
  • Estela Díaz-López
  • R. M. Molina-Ruíz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7930)


The field of Biomedical research is currently one with the greatest social impact and publication volume, providing continuous advances and results which should, to a great extent, reach the general clinical practice. Similarly, direct clinical experience may offer experimental results and conclusions which may lead, guide and foster new investigations. However, this interaction between research and clinical practice is yet too far from being optimal. On one side, research results are published without standardization, suffering terminological issues, which prevent its automatic handling and great scale information treatment/management. On the other, for the practitioner, the task of reviewing papers, bibliography, experimental results, etc. in order to keep updated his everyday clinical practice, is very time consuming, causing not to be done continuously.

The implantation of Information Technologies in the biomedical research field has developed numerous search and bibliographic management resources, existing a current trend towards building and publishing open access terminologies, ontological knowledge models and big datasets with biomedical content. All together, beside Semantic Web technologies, methodologies and Linked Open Data and AI techniques, conforms a technological framework which gives the opportunity to bridge the gap between research and clinical practice to support the physician in evidence based decision making.

In this work, as a starting point to the final aim of linking research and clinical practice, we describe a Semantic Bibliographical Recommender System (SBRS) based on patient profile integrated with electronic health record (EHR) which, without closing the loop, offers to the medical professional the latest and most significant experimental evidences related to his concrete case study. The system’s functionality and utility is exemplified through real life psychiatric cases, assisted by an expert psychiatrist.


Eating Disorder Anorexia Nervosa Eating Disorder Recommender System Electronic Health Record 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Santiago Timón-Reina
    • 1
  • Rafael Martínez-Tomás
    • 1
  • Mariano Rincón-Zamorano
    • 1
  • Tomás García-Sáiz
    • 1
  • Estela Díaz-López
    • 1
  • R. M. Molina-Ruíz
    • 1
  1. 1.Hospital Clínico San CarlosUNEDSpain

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