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Donnerstag, 11. September 2025: Die Deutsche Nationalbibliothek öffnet wegen eines Beschäftigtentreffens an beiden Standorten erst um 15 Uhr. // Thursday, 11 September 2025: The German National Library will not open until 15:00 due to a staff meeting at both locations.

Ergebnis der Suche nach: "Machine Learning"
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16651 - 16660 von 17035

	16651	Ultrasound-based radiomics machine learning models for diagnosing cervical lymph node metastasis in patients with non-small cell lung cancer: a multicentre study Enthalten in BMC cancer Bd. 24, 27.4.2024, Nr. 1, date:12.2024: 1-11
	16652	Unbiased identification of risk factors for invasive Escherichia coli disease using machine learning Enthalten in BMC infectious diseases Bd. 24, 8.8.2024, Nr. 1, date:12.2024: 1-12
	16653	Unbinned multivariate observables for global SMEFT analyses from machine learning Enthalten in Journal of high energy physics Bd. 2023, 6.3.2023, Nr. 3, date:3.2023: 1-66
	16654	Unboxing machine learning models for concrete strength prediction using XAI Enthalten in Scientific reports Bd. 13, 14.11.2023, Nr. 1, date:12.2023: 1-20
	16655	Uncertainty-aware approach for multiple imputation using conventional and machine learning models: a real-world data study Enthalten in Journal of Big Data Bd. 12, 17.4.2025, Nr. 1, date:12.2025: 1-28
	16656	Uncertainty-aware mixed-variable machine learning for materials design Enthalten in Scientific reports Bd. 12, 17.11.2022, Nr. 1, date:12.2022: 1-13
	16657	Uncertainty-Based Performance Prediction and Optimization of High-Fluidization Cement Grouting Material Using Machine Learning and Bayesian Inference Enthalten in International journal of concrete structures and materials Bd. 16, 7.12.2022, Nr. 1, date:12.2022: 1-15
	16658	Uncertainty quantification for probabilistic machine learning in earth observation using conformal prediction Enthalten in Scientific reports Bd. 14, 13.7.2024, Nr. 1, date:12.2024: 1-13
	16659	Unconfined compressive strength prediction of rock materials based on machine learning Enthalten in Journal of engineering and applied science Bd. 71, 19.6.2024, Nr. 1, date:12.2024: 1-32
	16660	Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality Enthalten in Molecular cancer Bd. 20, 28.8.2021, Nr. 1, date:12.2021: 1-22

16651 - 16660 von 17035

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