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Ergebnis der Suche nach: "Machine Learning"
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38551 - 38560 von 38915

	38551	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
	38552	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
	38553	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
	38554	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
	38555	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
	38556	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
	38557	Using machine-learning models to predict extubation failure in neonates with bronchopulmonary dysplasia Enthalten in BMC pulmonary medicine Bd. 24, 1.7.2024, Nr. 1, date:12.2024: 1-9
	38558	Using machine learning models to predict the impact of template mismatches on polymerase chain reaction assay performance Enthalten in Scientific reports Bd. 15, 9.5.2025, Nr. 1, date:12.2025: 1-11
	38559	Using machine learning of clinical data to diagnose COVID-19: a systematic review and meta-analysis Enthalten in BMC medical informatics and decision making Bd. 20, 29.9.2020, Nr. 1, date:12.2020: 1-13
	38560	Using machine learning on clinical data to identify unexpected patterns in groups of COVID-19 patients Enthalten in Scientific reports Bd. 13, 8.2.2023, Nr. 1, date:12.2023: 1-11

38551 - 38560 von 38915

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