Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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41581 - 41590 von 42063

	41581	Use of machine learning to improve the estimation of conductivity and permittivity based on longitudinal relaxation time T1 in magnetic resonance at 7 T Enthalten in Scientific reports Bd. 13, 15.5.2023, Nr. 1, date:12.2023: 1-17
	41582	Use of machine learning to predict creativity among nurses: a multidisciplinary approach Enthalten in BMC nursing Bd. 24, 15.5.2025, Nr. 1, date:12.2025: 1-12
	41583	USE OF MULTIVARIATE MACHINE LEARNING ANALYSIS TECHNIQUES FOR FLOOD RISK PREVENTION Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLII-3/W4, 2018: 549-554
	41584	Use of optimized machine learning tool for predicting compressive strength of concrete Enthalten in Asian journal of civil engineering Bd. 26, 29.7.2025, Nr. 11, date:11.2025: 4875-4895
	41585	Use of proper orthogonal decomposition and machine learning for efficient blood flow prediction in cerebral saccular aneurysms Enthalten in Scientific reports Bd. 15, 2.9.2025, Nr. 1, date:12.2025: 1-15
	41586	Use of structure-activity landscape index curves and curve integrals to evaluate the performance of multiple machine learning prediction models Enthalten in Journal of cheminformatics Bd. 3, 7.2.2011, Nr. 1, date:12.2011: 1-12
	41587	Use of systems with deep learning and machine learning for the detection and classification of malignant vs. benign spinal fractures with MRI: can deep/machine learning help us further for detection and characterization? Enthalten in European radiology Bd. 33, 26.5.2023, Nr. 7, date:7.2023: 5058-5059
	41588	Use of unsupervised machine learning to characterise HIV predictors in sub-Saharan Africa Enthalten in BMC infectious diseases Bd. 23, 19.7.2023, Nr. 1, date:12.2023: 1-13
	41589	Usefulness of machine learning softwares to screen titles of systematic reviews: a methodological study Enthalten in Systematic Reviews Bd. 12, 15.4.2023, Nr. 1, date:12.2023: 1-14
	41590	User structural information in priority-based ranking for top-N recommendation Enthalten in Advances in computational intelligence Bd. 3, 6.1.2023, Nr. 1, date:2.2023: 1-16

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