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

27621 - 27630 von 27902
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Artikel 27621 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
Online Ressource
Artikel 27622 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
Online Ressource
Artikel 27623 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
Online Ressource
Artikel 27624 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
Online Ressource
Artikel 27625 Using machine learning to translate tumor dependencies
Enthalten in Nature cancer Bd. 5, 23.7.2024, Nr. 8, date:8.2024: 1141-1142
Online Ressource
Artikel 27626 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
Online Ressource
Artikel 27627 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
Online Ressource
Artikel 27628 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
Online Ressource
Artikel 27629 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
Online Ressource
Artikel 27630 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
Online Ressource


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