Katalog der Deutschen Nationalbibliothek

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

17801 - 17810 von 17969

	17801	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
	17802	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
	17803	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
	17804	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
	17805	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
	17806	Using machine learning tools for protein database biocuration assistance Enthalten in Scientific reports Bd. 8, 5.7.2018, Nr. 1, date:12.2018: 1-10
	17807	Using machine learning tools to predict outcomes for emergency department intensive care unit patients Enthalten in Scientific reports Bd. 10, 1.12.2020, Nr. 1, date:12.2020: 1-10
	17808	Using machine learning with case studies to identify practices that reduce greenhouse gas emissions across Australian grain production regions Enthalten in Agronomy for sustainable development Bd. 43, 20.3.2023, Nr. 2, date:4.2023: 1-11
	17809	Using matrix assisted laser desorption ionisation mass spectrometry combined with machine learning for vaccine authenticity screening Enthalten in npj vaccines Bd. 9, 28.8.2024, Nr. 1, date:12.2024: 1-14
	17810	Using mid-infrared spectroscopy and supervised machine-learning to identify vertebrate blood meals in the malaria vector, Anopheles arabiensis Enthalten in Malaria journal Bd. 18, 30.5.2019, Nr. 1, date:12.2019: 1-9