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    Leveraging Machine Learning for Exchange Rate Prediction: A Business and Financial Management Perspective in Nigeria by Adedeji Daniel Gbadebo

    Published 2025-01-01
    “…Methodology The paper employs Logistic Linear Regression, Support Vector Machine, Random Forest, and XGBoost algorithms to predict the univariate time series of Nigeria's exchange rate against the US dollar, using both hourly and daily data. …”
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    Mobile application based on KDD to predict high-crime areas and promote sustainability in citizen security in a district of Lima-Perú by Hugo Vega-Huerta, Javier Vilca Velasquez, Nicolas Anicama Espinoza, Gisella Luisa Elena Maquen-Niño, Luis Guerra-Grados, Jorge Pantoja-Collantes, Oscar Benito-Pacheco, Juan Carlos Lázaro-Guillermo, Adegundo Camara-Figueroa, Javier Cabrera-Díaz, Rubén Gil-Calvo, Frida López-Córdova

    Published 2025-08-01
    “…The data mining process follows the KDD methodology, which includes the stages of selection, preprocessing, transformation, data mining, evaluation and knowledge consolidation. Machine learning algorithms, such as Random Forest and Gradient Boosting, were used to make these predictions. …”
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    The impact of intravenous iodinated contrast agents on radiotherapy dose calculation and radiobiological effect predictions in central lung cancer by Defu Yang, Feng Shang, Ying Xu, Ying Yan

    Published 2025-08-01
    “…This study evaluates and compares dosimetric differences and predictions of Tumor Control Probability (TCP) and Normal Tissue Complication Probability (NTCP) between the Analytic Anisotropic Algorithm (AAA) and Acuros XB (AXB) algorithm in lung cancer radiotherapy, under both contrast-enhanced and non-contrast enhanced CT conditions.MethodsTwenty patients with centralized lung cancer treated with intensity-modulated radiation therapy (IMRT) technique, including two patients with small cell lung cancer and 18 with non-small cell lung cancer, were selected to undergo CT scanning with and without contrast. …”
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    A Data-Driven Strategy for Long-Term Agrarian Sustainability using the Application of Machine Learning Algorithms to Predictive Models for Pest and Disease Management by Almusawi Muntather, Ameer S. Abdul, Lalitha Yaragudipati Sri

    Published 2025-01-01
    “…PDM-MLA based on predictive modeling predicts infestations with high accuracy by analyzing weather, parameters of soil, history of outbreaks of pests, and crop health data. …”
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    Construction of Clinical Predictive Models for Heart Failure Detection Using Six Different Machine Learning Algorithms: Identification of Key Clinical Prognostic Features by Qu FZ, Ding J, An XF, Peng R, He N, Liu S, Jiang X

    Published 2024-12-01
    “…Following the elimination of features with significant missing values, the remaining features were utilized to construct predictive models employing six machine learning algorithms. …”
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