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    The protocol for a multicentre prospective randomized noninferiority trial of surgical reduction versus non-surgical casting for displaced distal radius fractures in children: Chil... by Daniel C. Perry, Juul Achten, James Mason, Daphne Kounail, Nicolas Nicolaou, David Metcalfe, Mark Lyttle, Elizabeth Tutton, Duncan Appelbe, Phoebe Gibson, Matthew L. Costa

    Published 2025-05-01
    “…The primary outcome is the PROMIS Upper Extremity Score at three months post-randomization. All data will be obtained through electronic questionnaires completed by the participants and/or parents/guardians. …”
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    Machine Learning in the National Economy by Azamjon A. Usmonov

    Published 2025-07-01
    “…The main methods include an analysis of scientific literature, statistical data analysis, modeling using machine learning algorithms, and practical implementation of economic models with programming languages such as Python and machine learning libraries.To analyze economic data, methods such as linear regression, decision trees, and neural networks were selected, as they effectively predict changes in key macroeconomic indexes such as GDP, inflation, exchange rates, and unemployment levels. …”
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    House Price Prediction of Real Time Data (DHA Defence) Karachi Using Machine Learning by Lata Bai Gokalani, Bhagwan Das, Dilip Kumar Ramnani, Mahender Kumar, Mazhar Ali Shah

    Published 2022-12-01
    “…It is one of the main contribution of the work is that through this the house prediction model based on DHA Karachi data is developed and as per best of our knowledge till today there is no prediction of housing for the country’s important has been developed. has This research paper mainly focuses on real time Defense Housing Authority (DHA) Karachi data, applying different regression algorithms like Decision tree, Random forest and linear regression to find the sales price prediction of the house and compare the performance of these models. …”
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    Enhancing Software Defect Prediction Using Ensemble Techniques and Diverse Machine Learning Paradigms by Ayesha Siddika, Momotaz Begum, Fahmid Al Farid, Jia Uddin, Hezerul Abdul Karim

    Published 2025-07-01
    “…In supervised learning, we mainly experimented with several algorithms, including random forest, k-nearest neighbors, support vector machines, logistic regression, gradient boosting, AdaBoost classifier, quadratic discriminant analysis, Gaussian training, decision tree, passive aggressive, and ridge classifier. …”
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