Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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41651 - 41660 von 42063

	41651	Using machine learning involving diagnoses and medications as a risk prediction tool for post-acute sequelae of COVID-19 (PASC) in primary care Enthalten in BMC medicine Bd. 23, 30.4.2025, Nr. 1, date:12.2025: 1-12
	41652	Using machine learning method to predict food waste in catering industry under high resolution: a case in Dongguan Enthalten in Journal of material cycles and waste management Bd. 25, 20.5.2023, Nr. 4, date:7.2023: 2442-2456
	41653	Using Machine Learning Methods to Develop an Algorithm for Recognizing a Risk of Waterspout Occurrence off the Black Sea Coast of Russia Enthalten in Russian meteorology and hydrology Bd. 49, 27.6.2024, Nr. 4, date:4.2024: 363-369
	41654	Using machine learning methods to predict 28-day mortality in patients with hepatic encephalopathy Enthalten in BMC gastroenterology Bd. 23, 6.4.2023, Nr. 1, date:12.2023: 1-11
	41655	Using machine learning methods to predict electric vehicles penetration in the automotive market Enthalten in Scientific reports Bd. 13, 23.5.2023, Nr. 1, date:12.2023: 1-16
	41656	Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU Enthalten in BMC medical informatics and decision making Bd. 20, 2.10.2020, Nr. 1, date:12.2020: 1-10
	41657	Using Machine Learning Methods to Predict the Ductile-to-Brittle Transition Temperature Shift in RPV Steel Under Different Pulse Current Parameters Enthalten in Acta metallurgica Sinica / English letters Bd. 38, 24.4.2025, Nr. 6, date:6.2025: 1029-1040
	41658	Using Machine Learning Methods to Predict the Magnitude and the Direction of Mask Fragments Displacement in Optical Proximity Correction (OPC) Enthalten in Optical memory and neural networks Bd. 30, 29.12.2021, Nr. 4, date:10.2021: 291-297
	41659	Using machine learning model explanations to identify proteins related to severity of meibomian gland dysfunction Enthalten in Scientific reports Bd. 13, 22.12.2023, Nr. 1, date:12.2023: 1-13
	41660	Using machine learning models based on cardiac magnetic resonance parameters to predict the prognostic in children with myocarditis Enthalten in BMC pediatrics Bd. 25, 24.5.2025, Nr. 1, date:12.2025: 1-12

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