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    Machine learning algorithms for predictive modeling of dyslipidemia-associated cardiovascular disease risk in pregnancy: a comparison of boosting, random forest, and decision tree regression by Idris Zubairu Sadiq, Fatima Sadiq Abubakar, Muhammad Auwal Saliu, Babangida Sanusi katsayal, Aliyu Salihu, Aliyu Muhammad

    Published 2025-01-01
    “…Methods In this study, we utilized three different machine learning algorithms (boosting, random forest, and decision tree regression) to predict dyslipidemia-associated cardiovascular disease using atherogenic index and lipid profile parameters based on a cross-sectional study datasets of 112 pregnant women aged between 15 and 49 conducted at Aminu Kano Teaching Hospital. …”
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    Text Message System for the Prediction of Colonoscopy Bowel Preparation Adequacy Before Colonoscopy: An Artificial Intelligence Image Classification Algorithm Based on Images of Stool Output by Chethan Ramprasad, Divya Saini, Henry Del Carmen, Lev Krasnovsky, Rajat Chandra, Ryan Mcgregor, Russell T. Shinohara, Eric Eaton, Meghna Gummadi, Shivan Mehta, James D. Lewis

    Published 2025-01-01
    “…We aim to develop an artificial intelligence (machine learning) algorithm to assess photos of stool output after bowel preparation to predict inadequate bowel preparation before colonoscopy. …”
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  6. 1506

    Research on the Gas Emission Quantity Prediction Model of Improved Artificial Bee Colony Algorithm and Weighted Least Squares Support Vector Machine (IABC-WLSSVM) by Lei Wang, Jinghang Li, Wenbo Zhang, Yu Li

    Published 2022-01-01
    “…In order to further accurately predict gas emission of working face, this paper proposes a prediction model of gas emission of working face based on the combination of improved artificial bee colony algorithm and weighted least squares support vector machine (IABC-WLSSAVM). …”
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  7. 1507

    Application of Extra-Trees Regression and Tree-Structured Parzen Estimators Optimization Algorithm to Predict Blast-Induced Mean Fragmentation Size in Open-Pit Mines by Madalitso Mame, Shuai Huang, Chuanqi Li, Jian Zhou

    Published 2025-07-01
    “…The prediction accuracy of the models is optimized utilizing the tree-structured Parzen estimators (TPEs) algorithm, which results in three models: TPE-ET, TPE-GB, and TPE-RF. …”
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    Hybrid-driven modeling using a BiLSTM–AdaBoost algorithm for diameter prediction in the constant diameter stage of Czochralski silicon single crystals by Yu-Yu Liu, Ding Liu, Shi-Hai Wu, Yi-Ming Jing

    Published 2025-05-01
    “…Subsequently, the prediction results of the BiLSTM network are weighted and fused by the AdaBoost algorithm to obtain the final time series prediction output, and the prediction performance is further enhanced by iterative optimization. …”
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    Prediction of carbon dioxide emissions from Atlantic Canadian potato fields using advanced hybridized machine learning algorithms – Nexus of field data and modelling by Muhammad Hassan, Khabat Khosravi, Aitazaz A. Farooque, Travis J. Esau, Alaba Boluwade, Rehan Sadiq

    Published 2024-12-01
    “…In this study, three novel machine learning algorithms of additive regression-random forest (AR-RF), Iterative Classifier Optimizer (ICO-AR-RF), and multi-scheme (MS-RF) were explored for carbon dioxide (CO2) flux rate prediction from three agricultural fields. …”
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  14. 1514

    Predicting the risk of gastroparesis in critically ill patients after CME using an interpretable machine learning algorithm – a 10-year multicenter retrospective study by Yuan Liu, Songyun Zhao, Wenyi Du, Wei Shen, Ning Zhou

    Published 2025-01-01
    “…In the present study, four advanced machine learning algorithms—Extreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), and k-nearest neighbor (KNN)—were employed to develop predictive models. …”
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    Development and optimization of a neural network model using genetic algorithm to predict the performance of a packed bed reactor treating sulphate-rich wastewater by Manoj Kumar, Rohil Saraf, Shishir Kumar Behera, Raja Das, Mansi Aliveli, Arindam Sinharoy, Eldon R. Rene, Ravi Krishnaiah, Kannan Pakshirajan

    Published 2024-12-01
    “…An artificial neural network (ANN) model with 3-14-2 topology was developed by training the experimental data through the Levenberg Marquardt (LM) algorithm. Using genetic algorithm (GA) with appropriate objective functions, optimal sets of inputs were obtained to ensure maximum RE at a minimum HRT. …”
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