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  • Open Access


    Fuzzy Logic-Based System for Liver Fibrosis Disease

    Tamim Alkhalifah1,*, Jimmy Singla2, Fahad Alurise1

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3559-3582, 2023, DOI:10.32604/csse.2023.036534

    Abstract The diagnosis of liver fibrosis (LF) is crucial as it is a deadly and life-threatening disease. Artificial intelligence techniques aid doctors by using the previous data on health and making a diagnostic system, which helps to take decisions about patients’ health as experts can. The historical data of a patient’s health can have vagueness, inaccurate, and can also have missing values. The fuzzy logic theory can deal with these issues in the dataset. In this paper, a multilayer fuzzy expert system is developed to diagnose LF. The model is created by using multiple layers of… More >

  • Open Access


    Prediction System for Diagnosis and Detection of Coronavirus Disease-2019 (COVID-19): A Fuzzy-Soft Expert System

    Wencong Liu1, Ahmed Mostafa Khalil2,*, Rehab Basheer3, Yong Lin4

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2715-2730, 2023, DOI:10.32604/cmes.2023.024755

    Abstract In early December 2019, a new virus named “2019 novel coronavirus (2019-nCoV)” appeared in Wuhan, China. The disease quickly spread worldwide, resulting in the COVID-19 pandemic. In the current work, we will propose a novel fuzzy soft modal (i.e., fuzzy-soft expert system) for early detection of COVID-19. The main construction of the fuzzy-soft expert system consists of five portions. The exploratory study includes sixty patients (i.e., forty males and twenty females) with symptoms similar to COVID-19 in (Nanjing Chest Hospital, Department of Respiratory, China). The proposed fuzzy-soft expert system depended on five symptoms of COVID-19 More > Graphic Abstract

    Prediction System for Diagnosis and Detection of Coronavirus Disease-2019 (COVID-19): A Fuzzy-Soft Expert System

  • Open Access


    Modeling of a Fuzzy Expert System for Choosing an Appropriate Supply Chain Collaboration Strategy

    Kazim Sari

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 405-412, 2018, DOI:10.1080/10798587.2017.1352258

    Abstract Nowadays, there has been a great interest for business enterprises to work together or collaborate in the supply chain. It is thus possible for them to gain a competitive advantage in the marketplace. However, determining the right collaboration strategy is not an easy task. Namely, there are several factors that need to be considered at the same time. In this regard, an expert system based on fuzzy rules is proposed to choose an appropriate collaboration strategy for a given supply chain. To this end, firstly, the factors that are significant for supply chain collaboration are More >

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