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    Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

    Published 2025-02-01
    “…Machine learning (ML) has demonstrated potential in predicting SSIs; however, the challenge of addressing imbalanced class ratios remains. …”
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    Predicting student performance academic using Automated Machine Learning (AutoML): in medical academic institutions by Rania A. Abougalala, Nouf Alharbi, Mohamed A. Amasha, Marwa F. Areed, Salem Alkhalaf, Dalia Khairy

    Published 2025-08-01
    “…Abstract Educational institutions seek to increase distinguished educational programs, and these programs increase costs and expenses of these institutions consuming a lot of their budget. …”
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    Development and validation of a prediction model for coronary heart disease risk in depressed patients aged 20 years and older using machine learning algorithms by Yicheng Wang, Yicheng Wang, Yicheng Wang, Chuan-Yang Wu, Hui-Xian Fu, Jian-Cheng Zhang, Jian-Cheng Zhang, Jian-Cheng Zhang

    Published 2025-01-01
    “…Several evaluation metrics were employed to assess and compare the performance of eight different machine learning models, aiming to identify the most effective algorithm for predicting coronary heart disease risk in individuals with depression. …”
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    Real-Time Optimization Improved Model Predictive Control Trajectory Tracking for a Surface and Underwater Joint Observation System Based on Genetic Algorithm–Fuzzy Control by Qichao Wu, Yunli Nie, Shengli Wang, Shihao Zhang, Tianze Wang, Yizhe Huang

    Published 2025-03-01
    “…Aiming at the high-precision trajectory tracking problem of the new surface and underwater joint observation system (SUJOS) in the ocean remote sensing monitoring mission under complex sea conditions, especially at the problem of excessive tracking errors and slow convergence of actual trajectory oscillations caused by the wide range of angular changes in the motion trajectory, a real-time optimization improved model predictive control (IMPC) trajectory tracking method based on fuzzy control is proposed. …”
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    Prediction of new candidate proteins and analysis of sub-modules and protein hubs associated with seed development in rice (Oryza sativa) using an ensemble network-based systems bi... by M. R. P. De Silva, J. W. J. K. Weeraman, S. Piyatissa, P. C. Fernando

    Published 2025-05-01
    “…Using a list of known seed development proteins from the Gene Ontology (GO) knowledgebase and literature, novel candidate proteins for seed development were predicted using an ensemble of network-based algorithms, including Majority Voting, Hishigaki Algorithm, Functional Flow, and Random Walk with Restart, which were selected based on their popularity and usability. …”
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