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International Conference on Technologies and Innovation

CITI 2017: Technologies and Innovation pp 60–71Cite as

A Collaborative Filtering Based Recommender System for Disease Self-management

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 749))

Abstract

Diabetes is a chronic disease that is diagnosed by observing raised levels of glucose in the blood. High levels of glucose in the blood damage many tissues in the body, thus bringing life-threating and disabling health complications. According to the World Health Organization, the number of people with diabetes is around 422 million, and the diabetes prevalence has been raising more rapidly in middle and low-income countries. People with diabetes must have periodic contact with healthcare professionals. However, it is necessary for them to have the skills, attitude, and support for self-management. In other words, people with diabetes should be active participants in the treatment. In this work, we present a system for diabetes self-management. This system deals with different subjects related to the control and management of glucose levels in the blood, such as diet, physical activity, mood, medication, and treatment. Furthermore, this system implements the collaborative filtering recommendation algorithm for generating health recommendations. This module was evaluated to measure its effectiveness providing such recommendations obtaining encouraging results. This evaluation involved the participation of real patients with diabetes and healthcare professionals.

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Acknowledgments

This work has been funded by the Universidad de Guayaquil (Ecuador) through the project entitled “Tecnologías inteligentes para la autogestión de la salud”. Finally, this work has been also partially supported by the Spanish National Research Agency (AEI) and the European Regional Development Fund (FEDER / ERDF) through project KBS4FIA (TIN2016-76323-R).

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Authors and Affiliations

  1. Universidad de Guayaquil. Cdla. Universitaria Salvador Allende, Guayaquil, Ecuador

    José Medina-Moreira, Oscar Apolinario, Harry Luna-Aveiga & Katty Lagos-Ortiz

  2. Facultad de Informática. Universidad de Murcia. Campus de Espinardo, 30100, Murcia, Spain

    Mario Andrés Paredes-Valverde & Rafael Valencia-García

Authors
  1. José Medina-Moreira
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  2. Oscar Apolinario
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  3. Harry Luna-Aveiga
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  4. Katty Lagos-Ortiz
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  5. Mario Andrés Paredes-Valverde
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  6. Rafael Valencia-García
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Corresponding author

Correspondence to José Medina-Moreira .

Editor information

Editors and Affiliations

  1. Universidad de Murcia, Murcia, Spain

    Rafael Valencia-García

  2. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Katty Lagos-Ortiz

  3. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Gema Alcaraz-Mármol

  4. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Javier Del Cioppo

  5. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Néstor Vera-Lucio

  6. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Martha Bucaram-Leverone

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Medina-Moreira, J., Apolinario, O., Luna-Aveiga, H., Lagos-Ortiz, K., Paredes-Valverde, M.A., Valencia-García, R. (2017). A Collaborative Filtering Based Recommender System for Disease Self-management. In: Valencia-García, R., Lagos-Ortiz, K., Alcaraz-Mármol, G., Del Cioppo, J., Vera-Lucio, N., Bucaram-Leverone, M. (eds) Technologies and Innovation. CITI 2017. Communications in Computer and Information Science, vol 749. Springer, Cham. https://doi.org/10.1007/978-3-319-67283-0_5

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  • DOI: https://doi.org/10.1007/978-3-319-67283-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67282-3

  • Online ISBN: 978-3-319-67283-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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