Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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36551 - 36560 von 36845

	36551	Using machine learning to predict subsequent events after EMS non-conveyance decisions Enthalten in BMC medical informatics and decision making Bd. 22, 23.6.2022, Nr. 1, date:12.2022: 1-12
	36552	Using machine learning to predict the probability of incident 2-year depression in older adults with chronic diseases: a retrospective cohort study Enthalten in BMC psychiatry Bd. 24, 2.12.2024, Nr. 1, date:12.2024: 1-11
	36553	Using machine learning to predict the risk of short-term and long-term death in acute kidney injury patients after commencing CRRT Enthalten in BMC nephrology Bd. 25, 30.7.2024, Nr. 1, date:12.2024: 1-10
	36554	Using machine learning to predict venous thromboembolism and major bleeding events following total joint arthroplasty Enthalten in Scientific reports Bd. 13, 7.2.2023, Nr. 1, date:12.2023: 1-11
	36555	Using Machine Learning to Score Multi-Dimensional Assessments of Chemistry and Physics Enthalten in Journal of science education and technology Bd. 30, 26.3.2021, Nr. 2, date:4.2021: 239-254
	36556	Using machine learning to simultaneously quantify multiple cognitive components of episodic memory Enthalten in Nature Communications Bd. 16, 24.3.2025, Nr. 1, date:12.2025: 1-14
	36557	Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene expression in the developing C. elegans embryo Enthalten in BMC bioinformatics Bd. 11, 11.2.2010, Nr. 1, date:12.2010: 1-13
	36558	Using machine learning to translate tumor dependencies Enthalten in Nature cancer Bd. 5, 23.7.2024, Nr. 8, date:8.2024: 1141-1142
	36559	Using machine learning to understand social isolation and loneliness in schizophrenia, bipolar disorder, and the community Enthalten in Schizophrenia Bd. 10, 5.10.2024, Nr. 1, date:12.2024: 1-8
	36560	Using machine learning to understand the temporal morphology of the PM2.5 annual cycle in East Asia Enthalten in Environmental monitoring and assessment Bd. 191, 28.6.2019, Nr. 2, date:6.2019: 1-14