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Ergebnis der Suche nach: "Machine Learning"
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16561 - 16570 von 16715
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Artikel 16561 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 16562 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 16563 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 16564 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 16565 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
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Artikel 16566 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 16567 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
Artikel 16568 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
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Artikel 16569 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
Online Ressource
Artikel 16570 Using natural history to guide supervised machine learning for cryptic species delimitation with genetic data
Enthalten in Frontiers in zoology Bd. 19, 22.2.2022, Nr. 1, date:12.2022: 1-15
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