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A clinical decision-support system for dengue based on fuzzy cognitive maps

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Abstract

Dengue is a viral infection widely distributed in tropical and subtropical regions of the world. Dengue is characterized by high fatality rates when the diagnosis is not made promptly and effectively. To aid in the diagnosis of dengue, we propose a clinical decision-support system that classifies the clinical picture based on its severity, and using causal relationships evaluates the behavior of the clinical and laboratory variables that describe the signs and symptoms related to dengue. The system is based on a fuzzy cognitive map that is defined by the signs, symptoms and laboratory tests used in the conventional diagnosis of dengue. The evaluation of the model was performed on datasets of patients diagnosed with dengue to compare the model with other approaches. The developed model showed a good classification performance with 89.4% accuracy and could evaluate the behaviour of clinical and laboratory variables related to dengue severity (it is an explainable method). This model serves as a diagnostic aid for dengue that can be used by medical professionals in clinical settings.

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Acknowledgements

This study was partially funded by the Colombian Administrative Department of Science, Technology and Innovation - COLCIENCIAS (grant number 111572553478) (M. Toro) and Colombian Ministry of Science and Technology Bicentennial PhD Grant (W. Hoyos). The authors are grateful to physicians for using their knowledge and experience to build the FCMs and interpreting the final results.

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Authors and Affiliations

  1. Grupo de Investigaciones Microbiológicas y Biomédicas de Córdoba, Universidad de Córdoba, Carrera 6 No 77-305, Montería, Colombia

    William Hoyos

  2. Grupo de Investigación en I+D+i en TIC, Universidad EAFIT, Carrera 48 No 7Sur-50, Medellín, Colombia

    William Hoyos, Jose Aguilar & Mauricio Toro

  3. Centro de Estudios en Microelectrónica y Sistemas Distribuidos, Universidad de Los Andes, Núcleo La Hechicera, Mérida, Venezuela

    Jose Aguilar

  4. Departamento de Automática, Universidad de Alcalá, Alcalá de Henares, Spain

    Jose Aguilar

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  1. William Hoyos
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Contributions

William Hoyos: Conceptualization, Methodology, Software, Formal analysis, Investigation, Data curation, Validation, Visualization & Writing - original draft. Jose Aguilar: Conceptualization, Methodology, Formal analysis, Investigation, Resources, Supervision, Writing – reviewing & editing. Mauricio Toro: Conceptualization, Resources, Supervision, Writing - reviewing & editing.

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Correspondence to Jose Aguilar.

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Hoyos, W., Aguilar, J. & Toro, M. A clinical decision-support system for dengue based on fuzzy cognitive maps. Health Care Manag Sci 25, 666–681 (2022). https://doi.org/10.1007/s10729-022-09611-6

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