Tesis doctoralsDepartament d'Enginyeria Informàtica i Matemàtiques

Development of Machine Learning Techniques for Diabetic Retinopathy Risk Estimation

  • Identification data

    Identifier:  TDX:3311
    Authors:  Saleh Ali Ali, Emran
    Abstract:
    Diabetic retinopathy (DR) is a chronic illness. It is one of the main complications of diabetes, and an essential cause of vision loss among people suffering from diabetes. Diabetic patients must be periodically screened in order to detect signs of diabetic retinopathy development in an early stage. Early and frequent screening decreases the risk of vision loss and minimizes the load on the health care centres. The number of the diabetic patients is huge and rapidly increasing so that makes it hard and resource-consuming to perform a yearly screening to all of them. The main goal of this Ph.D. thesis is to build a clinical decision support system (CDSS) based on electronic health record (EHR) data. This CDSS will be utilised to estimate the risk of developing RD. In this Ph.D. thesis, I focus on developing novel interpretable machine learning systems. Fuzzy based systems with linguistic terms are going to be proposed. The output of such systems makes the physician know what combinations of the features that can cause the risk of developing DR. In this work, I propose a method to reduce the uncertainty in classifying diabetic patients using fuzzy decision trees. A Fuzzy Random forest (FRF) approach is proposed as well to estimate the risk for developing DR. Several policies are going to be proposed to merge the classification results achieved by different Fuzzy Decision Trees (FDT) models to improve the quality of the final decision of our models, I propose three fuzzy measures that are used with Choquet and Sugeno integrals. The definition of these fuzzy measures is based on the confidence values of the rules. In particular, one of them is a decomposable fuzzy measure in which the hierarchical structure of the FDT is exploited to find the values of the fuzzy measure. Out of this Ph.D. work, we have built a CDSS software that may be installed in the health care centres and hospitals in order to evaluate and detect Diabetic Retinopathy at early stages.
  • Others:

    Publisher: Universitat Rovira i Virgili
    Date: 2020-11-09, 2021-01-26T12:08:40Z, 2021-01-26T12:08:40Z
    Identifier: http://hdl.handle.net/10803/670493
    Departament/Institute: Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili.
    Language: eng
    Author: Saleh Ali Ali, Emran
    Director: Romero Aroca, Pedro, Moreno Ribas, Antonio, Valls Mateu, Aida
    Source: TDX (Tesis Doctorals en Xarxa)
    Format: application/pdf, application/pdf, 140 p.
  • Keywords:

    Diabetic Retinopathy
    Fuzzy Measures
    Fuzzy Rule-based Systems
    Retinopatía diabética
    Medidas difusas
    Sistemas basados en reglas
    Retinopatia diabètica
    Mesures difuses
    Sistemes basats en regles
    Engineering and Architecture
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