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Health Recommendation System Framework for the Optimization of Medical Decisions

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Book cover Cognitive Computing

Part of the book series: Edition Informatik Spektrum ((EIS))

Abstract

The introduction of recommendation systems for the health sector has opened additional channels to improve the decision-making of physicians and administrators of the healthcare system. Web-based and mobile applications, social networks and virtual communities could improve these processes. The Internet provides a huge amount of information; therefore, the creation of intelligent mechanisms and tools, such as the ones proposed, allows physicians and the health sector to be better informed in the decision-making process while improving communication channels. In this work, a theoretical framework for the design and implementation of the so-called project MedicGate, a smart social network to optimize medical decisions using cognitive computing is presented. The expectation is that this initiative will have an impact on those responsible for the generation of health policies, by providing information and resources for decision-making through informed knowledge and feedback from the medical and academic sector.

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Notes

  1. 1.

    https://www.cochrane.org/

  2. 2.

    In economic theory, a “fair price” is the price at which both the buyer and the seller are happy with the transaction. Even though it is a subjective notion, in a transaction both parts are clear about the price they are willing to accept. With no agreement in the price (e.g., too high/too low) the transaction will not take place.

  3. 3.

    Undertreatment is defined as to inadequately treated or not frequently enough (Dayal and Hort 2015). Overtreatment refers to unnecessary medical treatment (Brownlee 2010).

  4. 4.

    https://www.amazon.com

  5. 5.

    https://www.spotify.com

  6. 6.

    https://www.cochrane.org/about-us

  7. 7.

    https://drupal.org

  8. 8.

    https://www.researchgate.net/

  9. 9.

    https://grouplens.org/

  10. 10.

    https://movielens.org/

  11. 11.

    https://booklens.umn.edu/

  12. 12.

    http://cyclopath.org/

  13. 13.

    https://www.ute.edu.ec/

  14. 14.

    https://www.cochrane.org/

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Acknowledgements

The authors would like to thank the members of Information System Research Group and the Human-IST Institute at the University of Fribourg for contributing with valuable thoughts and comments. We would also like to thank the Swiss Post and Universidad Tecnológica Equinoccial (UTE) for the institutional support to develop this project. Thanks also to Dámaris Intriago-Baldeón from the German Cancer Research Center for her valuable comments and recommendations.

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Authors and Affiliations

  1. Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador

    Luis Terán

  2. Human-IST Institute, University of Fribourg, Fribourg, Switzerland

    Luis Terán & Jhonny Pincay

  3. Swiss Paraplegic Research, Nottwil, Switzerland

    Diana Pacheco

  4. CE IT4Innovations, IRAFM, University of Ostrava, Ostrava, Czech Republic

    Martin Štěpnička

  5. Universidad Tecnológica Equinoccial, Quito, Ecuador

    Daniel Simancas-Racines

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  1. Luis Terán
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Correspondence to Luis Terán .

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Editors and Affiliations

  1. Human-IST Institut, Universität Fribourg, Fribourg, Switzerland

    Edy Portmann

  2. Human-IST Institut, Universität Fribourg, Fribourg, Switzerland

    Sara D'Onofrio

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Terán, L., Pincay, J., Pacheco, D., Štěpnička, M., Simancas-Racines, D. (2020). Health Recommendation System Framework for the Optimization of Medical Decisions. In: Portmann, E., D'Onofrio, S. (eds) Cognitive Computing. Edition Informatik Spektrum. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-27941-7_11

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