External validation of the QCovid 2 and 3 risk prediction algorithms for risk of COVID-19 hospitalisation and mortality in adults: a national cohort study in Scotland by Aziz Sheikh, Julia Hippisley-Cox, Chris Robertson, Holly Tibble, Colin R Simpson, Colin McCowan, Igor Rudan, Adeniyi Francis Fagbamigbe, Steven Kerr, Tristan Millington, Karen Jeffrey

“…Objective The QCovid 2 and 3 algorithms are risk prediction tools developed during the second wave of the COVID-19 pandemic that can be used to predict the risk of COVID-19 hospitalisation and mortality, taking vaccination status into account. …”
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Predictive Maintenance Algorithms, Artificial Intelligence Digital Twin Technologies, and Internet of Robotic Things in Big Data-Driven Industry 4.0 Manufacturing Systems by Marek Nagy, Marcel Figura, Katarina Valaskova, George Lăzăroiu

“…In Industry 4.0, predictive maintenance (PdM) is key to optimising production processes. …”
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Algorithm for predicting cardiovascular events in low/moderate risk patients using traditional and new factors: data from 10-year follow-up study by M. D. Smirnova, O. N. Svirida, T. V. Fofanova, Z. N. Blankova, E. B. Yarovaya, F. T. Ageev

“…To create an advanced algorithm for predicting cardiovascular events (CVE) in low/moderate risk patients using a complex of traditional and new factors.Material and methods. …”
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Enhanced data-driven shear strength predictive modeling framework for RCDBs using explainable boosting-based ensemble learning algorithms coupled with Bayesian optimization by Imad Shakir Abbood, Noorhazlinda Abd Rahman, B.H. Abu Bakar

“…To achieve this goal, four ensemble boosting ML algorithms, namely Gradient Boosting, HistGBoost, XGBoost, and LightGBM, were adopted for implementation. …”
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A hybrid model for short-term offshore wind power prediction combining Kepler optimization algorithm with variational mode decomposition and stochastic configuration networks by Bingbing Yu, Yonggang Wang, Jun Wang, Yuanchu Ma, Wenpeng Li, Weigang Zheng

Subjects: “…Short-term offshore wind power prediction…”
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Correction: Derivation and validation of an algorithm to predict transitions from community to residential long-term care among persons with dementia—A retrospective cohort study

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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

“…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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A Predictive Model for the Shear Capacity of Ultra-High-Performance Concrete Deep Beams Reinforced with Fibers Using a Hybrid ANN-ANFIS Algorithm by Hossein Mirzaaghabeik, Nuha S. Mashaan, Sanjay Kumar Shukla

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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

“…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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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

“…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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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

“…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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Smart home power management algorithm using real-time model predictive control for a stand-alone PV system with battery energy storage by Aziz Watil

Subjects: “…Home manager algorithm…”
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An adaptive prediction method for ultra-short-term generation power of power system based on the improved long- and short-term memory network of sparrow algorithm by Peipei Yang, Zhidong Chen, Wen Tang, Zongyang Liu, Bingrui He

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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

“…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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Continuous prediction of human knee joint angle using a sparrow search algorithm optimized random forest model based on sEMG signals by Liuyi Ling, Zhu Lin, Bin Feng, Liyu Wei, Li Jin, Yiwen Wang

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Mortality Risk Prediction in Patients With Antimelanoma Differentiation–Associated, Gene 5 Antibody–Positive, Dermatomyositis–Associated Interstitial Lung Disease: Algorithm Development and Validation by Hui Li, Ruyi Zou, Hongxia Xin, Ping He, Bin Xi, Yaqiong Tian, Qi Zhao, Xin Yan, Xiaohua Qiu, Yujuan Gao, Yin Liu, Min Cao, Bi Chen, Qian Han, Juan Chen, Guochun Wang, Hourong Cai

“…There is an urgent need for a reliable prediction model, accessible via an easy-to-use web-based tool, to evaluate the risk of death. …”
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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

“…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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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

“…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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The Field Attributes May not Accurately Predict the Need for Early Tracheostomy Tube Insertion in Severe TBI Patients: A New Insight With the Help of AI Algorithms by Adrina Habibzadeh, Sepehr Khademolhosseini, Reza Taheri, Amin Niakan, Saeed Tayebi Khorami, Hadis Ghasemi, HosseinAli Khalili

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Predicting the tensile properties of heat treated and non-heat treated LPBFed AlSi10Mg alloy using machine learning regression algorithms by Vijaykumar S. Jatti, A. Saiyathibrahim, Arvind Yadav, Murali Krishnan R., B. Jayaprakash, Sumit Kaushal, Vinaykumar S. Jatti, Ashwini V. Jatti, Savita V. Jatti, Abhinav Kumar, Soumaya Gouadria, Ebenezer Bonyah

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