Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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36331 - 36340 von 36520

	36331	Validation of a Natural Language Machine Learning Model for Safety Literature Surveillance Enthalten in Drug safety Bd. 47, 8.11.2023, Nr. 1, date:1.2024: 71-80
	36332	Validation of machine learning models for estimation of left ventricular ejection fraction on point-of-care ultrasound: insights on features that impact performance Enthalten in Echo Research and Practice Bd. 11, 28.3.2024, Nr. 1, date:12.2024: 1-10
	36333	Validation of machine learning models to detect amyloid pathologies across institutions Enthalten in Acta Neuropathologica Communications Bd. 8, 28.4.2020, Nr. 1, date:12.2020: 1-13
	36334	Validity of Machine Learning in Assessing Large Texts Through Sustainability Indicators Enthalten in Social indicators research Bd. 166, 26.1.2023, Nr. 2, date:4.2023: 323-337
	36335	Value and limitations of machine learning in high-frequency nutrient data for gap-filling, forecasting, and transport process interpretation Enthalten in Environmental monitoring and assessment Bd. 195, 27.6.2023, Nr. 7, date:7.2023: 1-18
	36336	Value of Geologically Derived Features in Machine Learning Facies Classification Enthalten in Mathematical geosciences Bd. 52, 16.11.2019, Nr. 1, date:1.2020: 5-29
	36337	Value of machine learning in predicting TAVI outcomes Enthalten in Netherlands heart journal Bd. 27, 20.5.2019, Nr. 9, date:9.2019: 443-450
	36338	Values and inductive risk in machine learning modelling: the case of binary classification models Enthalten in European journal for philosophy of science Bd. 11, 26.10.2021, Nr. 4, date:12.2021: 1-27
	36339	Van Krevelen diagrams based on machine learning visualize feedstock-product relationships in thermal conversion processes Enthalten in Communications chemistry Bd. 6, 13.12.2023, Nr. 1, date:12.2023: 1-11
	36340	Variability analysis of soil organic carbon content across land use types and its digital mapping using machine learning and deep learning algorithms Enthalten in Environmental monitoring and assessment Bd. 197, 10.4.2025, Nr. 5, date:5.2025: 1-32