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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 the fuzzy logic approach. This… 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 (i.e., shortness of breath, sore… More > Graphic Abstract

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

  • Open Access


    An Intelligent Medical Expert System Using Temporal Fuzzy Rules and Neural Classifier

    Praveen Talari1,*, A. Suresh2, M. G. Kavitha3

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1053-1067, 2023, DOI:10.32604/iasc.2023.027024

    Abstract As per World Health Organization report which was released in the year of 2019, Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabetes all over the world. Hence it is inferred that diabetes is rampant across the world with the majority of the world population being affected by it. Among the diabetics, it can be observed that a large number of people had failed to identify their disease in the initial stage itself and hence the disease level moved from Type-1 to Type-2. To avoid this situation, we… More >

  • Open Access


    Expert System for Stable Power Generation Prediction in Microbial Fuel Cell

    Kathiravan Srinivasan1, Lalit Garg2,*, Bor-Yann Chen3, Abdulellah A. Alaboudi4, N. Z. Jhanjhi5, Chang-Tang Chang6, B. Prabadevi1, N. Deepa1

    Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 17-30, 2021, DOI:10.32604/iasc.2021.018380

    Abstract Expert Systems are interactive and reliable computer-based decision-making systems that use both facts and heuristics for solving complex decision-making problems. Generally, the cyclic voltammetry (CV) experiments are executed a random number of times (cycles) to get a stable production of power. However, presently there are not many algorithms or models for predicting the power generation stable criteria in microbial fuel cells. For stability analysis of Medicinal herbs’ CV profiles, an expert system driven by the augmented K-means clustering algorithm is proposed. Our approach requires a dataset that contains voltage-current relationships from CV experiments on the related subjects (plants/herbs). This new… More >

  • Open Access


    Fuzzy Logic-Based Health Monitoring System for COVID’19 Patients

    M. Jayalakshmi1, Lalit Garg2,*, K. Maharajan3, K. Jayakumar4, Kathiravan Srinivasan5, Ali Kashif Bashir6, K. Ramesh7

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2431-2447, 2021, DOI:10.32604/cmc.2021.015352

    Abstract In several countries, the ageing population contour focuses on high healthcare costs and overloaded health care environments. Pervasive health care monitoring system can be a potential alternative, especially in the COVID-19 pandemic situation to help mitigate such problems by encouraging healthcare to transition from hospital-centred services to self-care, mobile care and home care. In this aspect, we propose a pervasive system to monitor the COVID’19 patient’s conditions within the hospital and outside by monitoring their medical and psychological situation. It facilitates better healthcare assistance, especially for COVID’19 patients and quarantined people. It identifies the patient’s medical and psychological condition based… More >

  • 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 extracted via an extensive review… More >

  • Open Access


    Feature Selection Method Based on Class Discriminative Degree for Intelligent Medical Diagnosis

    Shengqun Fang1, Zhiping Cai1,*, Wencheng Sun1, Anfeng Liu2, Fang Liu3, Zhiyao Liang4, Guoyan Wang5

    CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 419-433, 2018, DOI: 10.3970/cmc.2018.02289

    Abstract By using efficient and timely medical diagnostic decision making, clinicians can positively impact the quality and cost of medical care. However, the high similarity of clinical manifestations between diseases and the limitation of clinicians’ knowledge both bring much difficulty to decision making in diagnosis. Therefore, building a decision support system that can assist medical staff in diagnosing and treating diseases has lately received growing attentions in the medical domain. In this paper, we employ a multi-label classification framework to classify the Chinese electronic medical records to establish corresponding relation between the medical records and disease categories, and compare this method… More >

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