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A Cloud Fuzzy Logic Framework for Oral Disease Risk Assessment

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Fuzzy Logic and Applications (WILF 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11291))

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Abstract

This paper presents a fuzzy logic framework for dental caries and erosion risk assessment. Two interdependent modules are implemented within a cloud architecture. The first module is a fuzzy expert system designed for physicians and expert users, able to provide an active support in formulating risk judgements. The second module is oriented to generic users for oral health promotion. Conceptual ingredients of the fuzzy logic framework are principally defined by eliciting knowledge from a group of experts. The generation of rules involves both structured interviews and data driven learning procedures based on the use of neuro-fuzzy techniques.

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Authors and Affiliations

  1. Department of Theoretical and Applied Science, University of Insubria Varese, Varese, Italy

    Gloria Gonella, Elisabetta Binaghi & Alberto Vergani

  2. Department of Medicine and Surgery, University of Insubria Varese, Varese, Italy

    Irene Biotti & Luca Levrini

Authors
  1. Gloria Gonella
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  2. Elisabetta Binaghi
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  3. Alberto Vergani
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  4. Irene Biotti
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  5. Luca Levrini
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Corresponding author

Correspondence to Gloria Gonella .

Editor information

Editors and Affiliations

  1. Széchenyi István University, Győr, Hungary

    Robert Fullér

  2. Ca’ Foscari University of Venice, Venice, Italy

    Silvio Giove

  3. University of Genoa, Genoa, Italy

    Francesco Masulli

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Gonella, G., Binaghi, E., Vergani, A., Biotti, I., Levrini, L. (2019). A Cloud Fuzzy Logic Framework for Oral Disease Risk Assessment. In: Fullér, R., Giove, S., Masulli, F. (eds) Fuzzy Logic and Applications. WILF 2018. Lecture Notes in Computer Science(), vol 11291. Springer, Cham. https://doi.org/10.1007/978-3-030-12544-8_7

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  • DOI: https://doi.org/10.1007/978-3-030-12544-8_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-12543-1

  • Online ISBN: 978-3-030-12544-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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