Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
im Bestand: Gesamter Bestand

34411 - 34420 von 34739

	34411	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
	34412	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
	34413	Using machine learning prediction models for quality control: a case study from the automotive industry Enthalten in Computational management science Bd. 20, 16.3.2023, Nr. 1, date:12.2023: 1-28
	34414	Using machine-learning risk prediction models to triage the acuity of undifferentiated patients entering the emergency care system: a systematic review Enthalten in Diagnostic and prognostic research Bd. 4, 2.10.2020, Nr. 1, date:12.2020: 1-12
	34415	Using machine-learning strategies to solve psychometric problems Enthalten in Scientific reports Bd. 12, 7.11.2022, Nr. 1, date:12.2022: 1-9
	34416	Using Machine Learning Techniques for Rainfall Estimation Based on Microwave Links of Mobile Telecommunication Networks Enthalten in SN Computer Science Bd. 4, 9.11.2022, Nr. 1, date:1.2023: 1-17
	34417	Using machine learning techniques for rationalising phenotypic readouts from a rat sleeping model Enthalten in Journal of cheminformatics Bd. 5, 22.3.2013, Nr. 1, date:3.2013: 1
	34418	Using machine learning techniques for the classification of ultra-low concentrations of cannabis in biological fluids Enthalten in Neural computing & applications Bd. 36, 7.8.2024, Nr. 31, date:11.2024: 19691-19705
	34419	Using machine learning techniques in multi-hazards assessment of Golestan National Park, Iran Enthalten in Natural hazards Bd. 117, 11.6.2023, Nr. 3, date:7.2023: 3231-3255
	34420	Using Machine Learning techniques in phenomenological studies on flavour physics Enthalten in Journal of high energy physics Bd. 2022, 19.7.2022, Nr. 7, date:7.2022: 1-43