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Ergebnis der Suche nach: "Machine Learning"
im Bestand: Gesamter Bestand

41731 - 41740 von 42035

	41731	Using the artificial bee colony technique to optimize machine learning algorithms in estimating the mature weight of camels Enthalten in Tropical animal health and production Bd. 55, 17.2.2023, Nr. 2, date:4.2023: 1-10
	41732	Using the grouping function of machine learning algorithm to reduce the influence of information avoidance tendency during reading behavior Enthalten in Smart Learning Environments Bd. 10, 27.11.2023, Nr. 1, date:12.2023: 1-16
	41733	Using the risk of spatial extrapolation by machine-learning models to assess the reliability of model predictions for conservation Enthalten in Landscape ecology Bd. 38, 10.4.2023, Nr. 6, date:6.2023: 1363-1372
	41734	Using time-series chest radiographs and laboratory data by machine learning for identifying pulmonary infection and colonization of Acinetobacter baumannii Enthalten in Respiratory research Bd. 25, 3.1.2024, Nr. 1, date:12.2024: 1-11
	41735	Using topological data analysis and machine learning to predict customer churn Enthalten in Journal of Big Data Bd. 11, 7.11.2024, Nr. 1, date:12.2024: 1-31
	41736	Using transfer learning and dimensionality reduction techniques to improve generalisability of machine-learning predictions of mosquito ages from mid-infrared spectra Enthalten in BMC bioinformatics Bd. 24, 9.1.2023, Nr. 1, date:12.2023: 1-15
	41737	Using unsupervised machine learning methods to cluster cardio-metabolic profile of the middle-aged and elderly Chinese with general and central obesity Enthalten in BMC cardiovascular disorders Bd. 25, 27.10.2025, Nr. 1, date:12.2025: 1-13
	41738	Using unsupervised machine learning to classify behavioral risk markers of bacterial vaginosis Enthalten in Archives of gynecology and obstetrics Bd. 309, 3.2.2024, Nr. 3, date:3.2024: 1053-1063
	41739	Using visible and NIR hyperspectral imaging and machine learning for nondestructive detection of nutrient contents in sorghum Enthalten in Scientific reports Bd. 15, 19.2.2025, Nr. 1, date:12.2025: 1-14
	41740	Using weak signals to predict spontaneous breathing trial success: a machine learning approach Enthalten in Intensive Care Medicine Experimental Bd. 13, 18.3.2025, Nr. 1, date:12.2025: 1-14

41731 - 41740 von 42035

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