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Ergebnis der Suche nach: "Machine Learning"
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41671 - 41680 von 42084

	41671	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
	41672	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
	41673	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
	41674	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
	41675	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
	41676	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
	41677	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
	41678	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
	41679	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
	41680	Using machine learning models to improve stroke risk level classification methods of China national stroke screening Enthalten in BMC medical informatics and decision making Bd. 19, 10.12.2019, Nr. 1, date:12.2019: 1-7

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