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  • Open Access

    ARTICLE

    Ensemble Learning for Fetal Health Classification

    Mesfer Al Duhayyim1,*, Sidra Abbas2, Abdullah Al Hejaili3, Natalia Kryvinska4,*, Ahmad Almadhor5, Huma Mughal6

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 823-842, 2023, DOI:10.32604/csse.2023.037488 - 26 May 2023

    Abstract : Cardiotocography (CTG) represents the fetus’s health inside the womb during labor. However, assessment of its readings can be a highly subjective process depending on the expertise of the obstetrician. Digital signals from fetal monitors acquire parameters (i.e., fetal heart rate, contractions, acceleration). Objective:: This paper aims to classify the CTG readings containing imbalanced healthy, suspected, and pathological fetus readings. Method:: We perform two sets of experiments. Firstly, we employ five classifiers: Random Forest (RF), Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LGBM) without over-sampling to classify CTG… More >

  • Open Access

    ARTICLE

    Optimisation Strategy of Carbon Dioxide Methanation Technology Based on Microbial Electrolysis Cells

    Qifen Li, Xiaoxiao Yan*, Yongwen Yang, Liting Zhang, Yuanbo Hou

    Journal of Renewable Materials, Vol.11, No.7, pp. 3177-3191, 2023, DOI:10.32604/jrm.2023.027749 - 05 June 2023

    Abstract Microbial Electrolytic Cell (MEC) is an electrochemical reaction device that uses electrical energy as an energy input and microorganisms as catalysts to produce fuels and chemicals. The regenerative electrochemical system is a MEC improvement system for methane gas produced by biological carbon sequestration technology using renewable energy sources to provide a voltage environment. In response to the influence of fluctuating disturbances of renewable electricity and the long system start-up time, this paper analyzes the characteristics of two strategies, regulating voltage parameter changes and activated sludge pretreatment, on the methane production efficiency of the renewable gas… More >

  • Open Access

    ARTICLE

    Fatigue Life Estimation of High Strength 2090-T83 Aluminum Alloy under Pure Torsion Loading Using Various Machine Learning Techniques

    Mustafa Sami Abdullatef*, Faten N. Alzubaidi, Anees Al-Tamimi, Yasser Ahmed Mahmood

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.8, pp. 2083-2107, 2023, DOI:10.32604/fdmp.2023.027266 - 04 April 2023

    Abstract The ongoing effort to create methods for detecting and quantifying fatigue damage is motivated by the high levels of uncertainty in present fatigue-life prediction approaches and the frequently catastrophic nature of fatigue failure. The fatigue life of high strength aluminum alloy 2090-T83 is predicted in this study using a variety of artificial intelligence and machine learning techniques for constant amplitude and negative stress ratios (). Artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), support-vector machines (SVM), a random forest model (RF), and an extreme-gradient tree-boosting model (XGB) are trained using numerical and experimental input… More > Graphic Abstract

    Fatigue Life Estimation of High Strength 2090-T83 Aluminum Alloy under Pure Torsion Loading Using Various Machine Learning Techniques

  • Open Access

    ARTICLE

    An Improved Ensemble Learning Approach for Heart Disease Prediction Using Boosting Algorithms

    Shahid Mohammad Ganie1, Pijush Kanti Dutta Pramanik2, Majid Bashir Malik3, Anand Nayyar4, Kyung Sup Kwak5,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3993-4006, 2023, DOI:10.32604/csse.2023.035244 - 03 April 2023

    Abstract Cardiovascular disease is among the top five fatal diseases that affect lives worldwide. Therefore, its early prediction and detection are crucial, allowing one to take proper and necessary measures at earlier stages. Machine learning (ML) techniques are used to assist healthcare providers in better diagnosing heart disease. This study employed three boosting algorithms, namely, gradient boost, XGBoost, and AdaBoost, to predict heart disease. The dataset contained heart disease-related clinical features and was sourced from the publicly available UCI ML repository. Exploratory data analysis is performed to find the characteristics of data samples about descriptive and… More >

  • Open Access

    ARTICLE

    Early Detection of Alzheimer’s Disease Based on Laplacian Re-Decomposition and XGBoosting

    Hala Ahmed1, Hassan Soliman1, Shaker El-Sappagh2,3,4, Tamer Abuhmed4,*, Mohammed Elmogy1

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2773-2795, 2023, DOI:10.32604/csse.2023.036371 - 03 April 2023

    Abstract The precise diagnosis of Alzheimer’s disease is critical for patient treatment, especially at the early stage, because awareness of the severity and progression risks lets patients take preventative actions before irreversible brain damage occurs. It is possible to gain a holistic view of Alzheimer’s disease staging by combining multiple data modalities, known as image fusion. In this paper, the study proposes the early detection of Alzheimer’s disease using different modalities of Alzheimer’s disease brain images. First, the preprocessing was performed on the data. Then, the data augmentation techniques are used to handle overfitting. Also, the… More >

  • Open Access

    ARTICLE

    Machine-Learning-Enabled Obesity Level Prediction Through Electronic Health Records

    Saeed Ali Alsareii1, Muhammad Awais2,*, Abdulrahman Manaa Alamri1, Mansour Yousef AlAsmari1, Muhammad Irfan3, Mohsin Raza2, Umer Manzoor4

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3715-3728, 2023, DOI:10.32604/csse.2023.035687 - 03 April 2023

    Abstract Obesity is a critical health condition that severely affects an individual’s quality of life and well-being. The occurrence of obesity is strongly associated with extreme health conditions, such as cardiac diseases, diabetes, hypertension, and some types of cancer. Therefore, it is vital to avoid obesity and or reverse its occurrence. Incorporating healthy food habits and an active lifestyle can help to prevent obesity. In this regard, artificial intelligence (AI) can play an important role in estimating health conditions and detecting obesity and its types. This study aims to see obesity levels in adults by implementing… More >

  • Open Access

    ARTICLE

    An Automated System for Early Prediction of Miscarriage in the First Trimester Using Machine Learning

    Sumayh S. Aljameel1, Malak Aljabri1,2, Nida Aslam1, Dorieh M. Alomari3,*, Arwa Alyahya1, Shaykhah Alfaris1, Maha Balharith1, Hiessa Abahussain1, Dana Boujlea1, Eman S. Alsulmi4

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1291-1304, 2023, DOI:10.32604/cmc.2023.035710 - 06 February 2023

    Abstract Currently, the risk factors of pregnancy loss are increasing and are considered a major challenge because they vary between cases. The early prediction of miscarriage can help pregnant ladies to take the needed care and avoid any danger. Therefore, an intelligent automated solution must be developed to predict the risk factors for pregnancy loss at an early stage to assist with accurate and effective diagnosis. Machine learning (ML)-based decision support systems are increasingly used in the healthcare sector and have achieved notable performance and objectiveness in disease prediction and prognosis. Thus, we developed a model… More >

  • Open Access

    ARTICLE

    A Novel Gradient Boosted Energy Optimization Model (GBEOM) for MANET

    Neenavath Veeraiah1,*, Youseef Alotaibi2, Saleh Alghamdi3, Satish Thatavarti4

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 637-657, 2023, DOI:10.32604/csse.2023.034224 - 20 January 2023

    Abstract Mobile Ad Hoc Network (MANET) is an infrastructure-less network that is comprised of a set of nodes that move randomly. In MANET, the overall performance is improved through multipath multicast routing to achieve the quality of service (quality of service). In this, different nodes are involved in the information data collection and transmission to the destination nodes in the network. The different nodes are combined and presented to achieve energy-efficient data transmission and classification of the nodes. The route identification and routing are established based on the data broadcast by the network nodes. In transmitting… More >

  • Open Access

    ARTICLE

    A Two-Step Algorithm to Estimate Variable Importance for Multi-State Data: An Application to COVID-19

    Behnaz Alafchi1, Leili Tapak1,*, Hassan Doosti2, Christophe Chesneau3, Ghodratollah Roshanaei1

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2047-2064, 2023, DOI:10.32604/cmes.2022.022647 - 23 November 2022

    Abstract Survival data with a multi-state structure are frequently observed in follow-up studies. An analytic approach based on a multi-state model (MSM) should be used in longitudinal health studies in which a patient experiences a sequence of clinical progression events. One main objective in the MSM framework is variable selection, where attempts are made to identify the risk factors associated with the transition hazard rates or probabilities of disease progression. The usual variable selection methods, including stepwise and penalized methods, do not provide information about the importance of variables. In this context, we present a two-step More >

  • Open Access

    ARTICLE

    Copy Move Forgery Detection Using Novel Quadsort Moth Flame Light Gradient Boosting Machine

    R. Dhanya1,*, R. Kalaiselvi2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1577-1593, 2023, DOI:10.32604/csse.2023.031319 - 03 November 2022

    Abstract A severe problem in modern information systems is Digital media tampering along with fake information. Even though there is an enhancement in image development, image forgery, either by the photographer or via image manipulations, is also done in parallel. Numerous researches have been concentrated on how to identify such manipulated media or information manually along with automatically; thus conquering the complicated forgery methodologies with effortlessly obtainable technologically enhanced instruments. However, high complexity affects the developed methods. Presently, it is complicated to resolve the issue of the speed-accuracy trade-off. For tackling these challenges, this article put… More >

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