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  • Open Access

    ARTICLE

    Data and Ensemble Machine Learning Fusion Based Intelligent Software Defect Prediction System

    Sagheer Abbas1, Shabib Aftab1,2, Muhammad Adnan Khan3,4, Taher M. Ghazal5,6, Hussam Al Hamadi7, Chan Yeob Yeun8,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6083-6100, 2023, DOI:10.32604/cmc.2023.037933

    Abstract The software engineering field has long focused on creating high-quality software despite limited resources. Detecting defects before the testing stage of software development can enable quality assurance engineers to concentrate on problematic modules rather than all the modules. This approach can enhance the quality of the final product while lowering development costs. Identifying defective modules early on can allow for early corrections and ensure the timely delivery of a high-quality product that satisfies customers and instills greater confidence in the development team. This process is known as software defect prediction, and it can improve end-product quality while reducing the cost… More >

  • Open Access

    ARTICLE

    Data and Machine Learning Fusion Architecture for Cardiovascular Disease Prediction

    Munir Ahmad1, Majed Alfayad2, Shabib Aftab1,3, Muhammad Adnan Khan4,*, Areej Fatima5, Bilal Shoaib6, Mohammad Sh. Daoud7, Nouh Sabri Elmitwally2,8

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2717-2731, 2021, DOI:10.32604/cmc.2021.019013

    Abstract Heart disease, which is also known as cardiovascular disease, includes various conditions that affect the heart and has been considered a major cause of death over the past decades. Accurate and timely detection of heart disease is the single key factor for appropriate investigation, treatment, and prescription of medication. Emerging technologies such as fog, cloud, and mobile computing provide substantial support for the diagnosis and prediction of fatal diseases such as diabetes, cancer, and cardiovascular disease. Cloud computing provides a cost-efficient infrastructure for data processing, storage, and retrieval, with much of the extant research recommending machine learning (ML) algorithms for… More >

  • Open Access

    ARTICLE

    Cloud-Based Diabetes Decision Support System Using Machine Learning Fusion

    Shabib Aftab1,2, Saad Alanazi3, Munir Ahmad1, Muhammad Adnan Khan4,*, Areej Fatima5, Nouh Sabri Elmitwally3,6

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1341-1357, 2021, DOI:10.32604/cmc.2021.016814

    Abstract Diabetes mellitus, generally known as diabetes, is one of the most common diseases worldwide. It is a metabolic disease characterized by insulin deficiency, or glucose (blood sugar) levels that exceed 200 mg/dL (11.1 ml/L) for prolonged periods, and may lead to death if left uncontrolled by medication or insulin injections. Diabetes is categorized into two main types—type 1 and type 2—both of which feature glucose levels above “normal,” defined as 140 mg/dL. Diabetes is triggered by malfunction of the pancreas, which releases insulin, a natural hormone responsible for controlling glucose levels in blood cells. Diagnosis and comprehensive analysis of this… More >

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