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A Comparative Study of Two Rule-Based Explanation Methods for Diabetic Retinopathy Risk Assessment

  • Identification data

    Identifier: imarina:9261338
  • Authors:

    Maaroof N
    Moreno A
    Valls A
    Jabreel M
    Szelag M
  • Others:

    Author, as appears in the article.: Maaroof N; Moreno A; Valls A; Jabreel M; Szelag M
    Department: Enginyeria Informàtica i Matemàtiques
    URV's Author/s: Moreno Ribas, Antonio / Valls Mateu, Aïda
    Keywords: Machine learning Fuzzy rules Explainable ai Dominance-based rough set approach Diabetic retinopathy Decision-support-system machine learning fuzzy rules dominance-based rough set approach diabetic retinopathy
    Abstract: Understanding the reasons behind the decisions of complex intelligent systems is crucial in many domains, especially in healthcare. Local explanation models analyse a decision on a single instance, by using the responses of the system to the points in its neighbourhood to build a surrogate model. This work makes a comparative analysis of the local explanations provided by two rule-based explanation methods on RETIPROGRAM, a system based on a fuzzy random forest that analyses the health record of a diabetic person to assess his/her degree of risk of developing diabetic retinopathy. The analysed explanation methods are C-LORE-F (a variant of LORE that builds a decision tree) and DRSA (a method based on rough sets that builds a set of rules). The explored methods gave good results in several metrics, although there is room for improvement in the generation of counterfactual examples.
    Thematic Areas: Química Process chemistry and technology Physics, applied Materials science, multidisciplinary Materials science (miscellaneous) Materials science (all) Materiais Instrumentation General materials science General engineering Fluid flow and transfer processes Engineering, multidisciplinary Engineering (miscellaneous) Engineering (all) Engenharias ii Engenharias i Computer science applications Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências agrárias i Ciência de alimentos Chemistry, multidisciplinary Biodiversidade Astronomia / física
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: aida.valls@urv.cat antonio.moreno@urv.cat
    Author identifier: 0000-0003-3616-7809 0000-0003-3945-2314
    Record's date: 2023-02-19
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://www.mdpi.com/2076-3417/12/7/3358
    Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Applied Sciences-Basel. 12 (7):
    APA: Maaroof N; Moreno A; Valls A; Jabreel M; Szelag M (2022). A Comparative Study of Two Rule-Based Explanation Methods for Diabetic Retinopathy Risk Assessment. Applied Sciences-Basel, 12(7), -. DOI: 10.3390/app12073358
    Article's DOI: 10.3390/app12073358
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2022
    Publication Type: Journal Publications
  • Keywords:

    Chemistry, Multidisciplinary,Computer Science Applications,Engineering (Miscellaneous),Engineering, Multidisciplinary,Fluid Flow and Transfer Processes,Instrumentation,Materials Science (Miscellaneous),Materials Science, Multidisciplinary,Physics, Applied,Process Chemistry and Technology
    Machine learning
    Fuzzy rules
    Explainable ai
    Dominance-based rough set approach
    Diabetic retinopathy
    Decision-support-system
    machine learning
    fuzzy rules
    dominance-based rough set approach
    diabetic retinopathy
    Química
    Process chemistry and technology
    Physics, applied
    Materials science, multidisciplinary
    Materials science (miscellaneous)
    Materials science (all)
    Materiais
    Instrumentation
    General materials science
    General engineering
    Fluid flow and transfer processes
    Engineering, multidisciplinary
    Engineering (miscellaneous)
    Engineering (all)
    Engenharias ii
    Engenharias i
    Computer science applications
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências agrárias i
    Ciência de alimentos
    Chemistry, multidisciplinary
    Biodiversidade
    Astronomia / física
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