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24241 - 24250 von 24371

	24241	Using machine learning-based algorithms to construct cardiovascular risk prediction models for Taiwanese adults based on traditional and novel risk factors Enthalten in BMC medical informatics and decision making Bd. 24, 22.7.2024, Nr. 1, date:12.2024: 1-8
	24242	Using meta-learning for automated algorithms selection and configuration: an experimental framework for industrial big data Enthalten in Journal of Big Data Bd. 9, 29.4.2022, Nr. 1, date:12.2022: 1-20
	24243	Using metaheuristic algorithms to optimize a mixed model-based ground-motion prediction model and associated variance components Enthalten in Journal of seismology Bd. 26, 4.5.2022, Nr. 3, date:6.2022: 483-498
	24244	Using multi-objective evolutionary algorithms for single-objective constrained and unconstrained optimization Enthalten in Annals of operations research Bd. 240, 22.9.2015, Nr. 1, date:5.2016: 217-250
	24245	Using multi-objective evolutionary algorithms to predict the parameters that determine membrane resonance in a biophysical model of bursting neurons Enthalten in BMC neuroscience Bd. 15, 21.7.2014, Nr. 1, date:7.2014: 1-2
	24246	Using multivariate adaptive regression splines and extremely randomized trees algorithms to predict dust events frequency around an international wetland and prioritize its drivers Enthalten in Environmental monitoring and assessment Bd. 193, 22.6.2021, Nr. 7, date:7.2021: 1-21
	24247	Using Nondeterminism to Design Efficient Deterministic Algorithms Enthalten in Algorithmica Bd. 40, 16.4.2004, Nr. 2, date:10.2004: 83-97
	24248	Using of Genetic Algorithms for Adaptive Filter Selection in Special-Purpose Systems Enthalten in Russian journal of general chemistry Bd. 91, 17.1.2022, Nr. 12, date:12.2021: 2734-2736
	24249	Using Optimized Deep Learning to Predict Daily Streamflow: A Comparison to Common Machine Learning Algorithms Enthalten in Water resources management Bd. 36, 17.1.2022, Nr. 2, date:1.2022: 699-716
	24250	Using primary care data to evaluate the 10-year cost-effectiveness of cardiovascular disease risk algorithms in patients with serious mental illness: a patient level simulation Enthalten in Trials Bd. 16, 16.11.2015, Nr. 2, date:12.2015: 1

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