Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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16151 - 16160 von 16728

	16151	The interplay of machine learning-based resonant anomaly detection methods Enthalten in The European physical journal / C / Particles and fields Bd. 84, 8.3.2024, Nr. 3, date:3.2024: 1-21
	16152	The interpretable machine learning model for depression associated with heavy metals via EMR mining method Enthalten in Scientific reports Bd. 15, 28.3.2025, Nr. 1, date:12.2025: 1-11
	16153	The K-functional and saturated linear approximation processes Enthalten in Sampling theory, signal processing, and data analysis Bd. 21, 13.6.2023, Nr. 1, date:6.2023: 1-11
	16154	The machine learning horizon in cardiac hybrid imaging Enthalten in European journal of hybrid imaging Bd. 2, 23.7.2018, Nr. 1, date:12.2018: 1-15
	16155	The machine learning methods to analyze the using strategy of antiplatelet drugs in ischaemic stroke patients with gastrointestinal haemorrhage Enthalten in BMC neurology Bd. 23, 13.10.2023, Nr. 1, date:12.2023: 1-8
	16156	The mastery of details in the workflow of materials machine learning Enthalten in npj computational materials Bd. 10, 2.7.2024, Nr. 1, date:12.2024: 1-17
	16157	The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery Enthalten in Journal of translational medicine Bd. 22, 6.2.2024, Nr. 1, date:12.2024: 1-24
	16158	The metabolic clock of ketamine abuse in rats by a machine learning model Enthalten in Scientific reports Bd. 14, 14.8.2024, Nr. 1, date:12.2024: 1-12
	16159	The performance of some machine learning approaches and a rich context model in student answer prediction Enthalten in Research and practice in technology enhanced learning Bd. 16, 26.4.2021, Nr. 1, date:12.2021: 1-16
	16160	The performance of VCS(volume, conductivity, light scatter) parameters in distinguishing latent tuberculosis and active tuberculosis by using machine learning algorithm Enthalten in BMC infectious diseases Bd. 23, 16.12.2023, Nr. 1, date:12.2023: 1-9