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Integration of the Wang & Mendel Algorithm into the Application of Fuzzy Expert Systems to Intelligent Clinical Decision Support Systems

Author

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  • Manuel Casal-Guisande

    (Department of Design in Engineering, University of Vigo, 36208 Vigo, Spain
    Design, Expert Systems and Artificial Intelligent Solutions Group (DESAINS), Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36213 Vigo, Spain)

  • Jorge Cerqueiro-Pequeño

    (Department of Design in Engineering, University of Vigo, 36208 Vigo, Spain
    Design, Expert Systems and Artificial Intelligent Solutions Group (DESAINS), Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36213 Vigo, Spain)

  • José-Benito Bouza-Rodríguez

    (Department of Design in Engineering, University of Vigo, 36208 Vigo, Spain
    Design, Expert Systems and Artificial Intelligent Solutions Group (DESAINS), Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36213 Vigo, Spain)

  • Alberto Comesaña-Campos

    (Department of Design in Engineering, University of Vigo, 36208 Vigo, Spain
    Design, Expert Systems and Artificial Intelligent Solutions Group (DESAINS), Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36213 Vigo, Spain)

Abstract

The use of intelligent systems in clinical diagnostics has evolved, integrating statistical learning and knowledge-based representation models. Two recent works propose the identification of risk factors for the diagnosis of obstructive sleep apnea (OSA). The first uses statistical learning to identify indicators associated with different levels of the apnea-hypopnea index (AHI). The second paper combines statistical and symbolic inference approaches to obtain risk indicators ( Statistical Risk and Symbolic Risk ) for a given AHI level. Based on this, in this paper we propose a new intelligent system that considers different AHI levels and generates risk pairs for each level. A learning-based model generates Statistical Risks based on objective patient data, while a cascade of fuzzy expert systems determines a Symbolic Risk using symptom data from patient interviews. The aggregation of risk pairs at each level involves a fuzzy expert system with automatically generated fuzzy rules using the Wang-Mendel algorithm. This aggregation produces an Apnea Risk indicator for each AHI level, allowing discrimination between OSA and non-OSA cases, along with appropriate recommendations. This approach improves variability, usefulness, and interpretability, increasing the reliability of the system. Initial tests on data from 4400 patients yielded AUC values of 0.74–0.88, demonstrating the potential benefits of the proposed intelligent system architecture.

Suggested Citation

  • Manuel Casal-Guisande & Jorge Cerqueiro-Pequeño & José-Benito Bouza-Rodríguez & Alberto Comesaña-Campos, 2023. "Integration of the Wang & Mendel Algorithm into the Application of Fuzzy Expert Systems to Intelligent Clinical Decision Support Systems," Mathematics, MDPI, vol. 11(11), pages 1-33, May.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:11:p:2469-:d:1157360
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    References listed on IDEAS

    as
    1. Manuel Casal-Guisande & Alberto Comesaña-Campos & Alejandro Pereira & José-Benito Bouza-Rodríguez & Jorge Cerqueiro-Pequeño, 2022. "A Decision-Making Methodology Based on Expert Systems Applied to Machining Tools Condition Monitoring," Mathematics, MDPI, vol. 10(3), pages 1-30, February.
    2. Alberto Comesaña-Campos & Manuel Casal-Guisande & Jorge Cerqueiro-Pequeño & José-Benito Bouza-Rodríguez, 2020. "A Methodology Based on Expert Systems for the Early Detection and Prevention of Hypoxemic Clinical Cases," IJERPH, MDPI, vol. 17(22), pages 1-31, November.
    3. Jorge Cerqueiro-Pequeño & Alberto Comesaña-Campos & Manuel Casal-Guisande & José-Benito Bouza-Rodríguez, 2020. "Design and Development of a New Methodology Based on Expert Systems Applied to the Prevention of Indoor Radon Gas Exposition Risks," IJERPH, MDPI, vol. 18(1), pages 1-32, December.
    4. Sabri Boughorbel & Fethi Jarray & Mohammed El-Anbari, 2017. "Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-17, June.
    5. Denis Bouyssou & Thierry Marchant & Marc Pirlot & Alexis Tsoukiàs & Philippe Vincke, 2006. "Evaluation and Decision Models with Multiple Criteria," International Series in Operations Research and Management Science, Springer, number 978-0-387-31099-2, December.
    6. Manuel Casal-Guisande & María Torres-Durán & Mar Mosteiro-Añón & Jorge Cerqueiro-Pequeño & José-Benito Bouza-Rodríguez & Alberto Fernández-Villar & Alberto Comesaña-Campos, 2023. "Design and Conceptual Proposal of an Intelligent Clinical Decision Support System for the Diagnosis of Suspicious Obstructive Sleep Apnea Patients from Health Profile," IJERPH, MDPI, vol. 20(4), pages 1-31, February.
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    Cited by:

    1. Shuoyu Wang, 2024. "A New Distance-Type Fuzzy Inference Method Based on Characteristic Parameters," Mathematics, MDPI, vol. 12(2), pages 1-14, January.

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