Katalog der Deutschen Nationalbibliothek

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

16401 - 16410 von 16659

	16401	Use of machine learning techniques for identifying ischemic stroke instead of the rule-based methods: a nationwide population-based study Enthalten in European journal of medical research Bd. 29, 3.1.2024, Nr. 1, date:12.2024: 1-9
	16402	Use of machine learning techniques to identify HIV predictors for screening in sub-Saharan Africa Enthalten in BMC medical research methodology Bd. 21, 31.7.2021, Nr. 1, date:12.2021: 1-11
	16403	Use of machine learning to analyse routinely collected intensive care unit data: a systematic review Enthalten in Critical care Bd. 23, 22.8.2019, Nr. 1, date:12.2019: 1-11
	16404	Use of machine learning to assess factors affecting progression, retention, and graduation in first-year health professions students in Qatar: a longitudinal study Enthalten in BMC medical education Bd. 23, 30.11.2023, Nr. 1, date:12.2023: 1-11
	16405	Use of machine learning to classify adult ADHD and other conditions based on the Conners’ Adult ADHD Rating Scales Enthalten in Scientific reports Bd. 10, 2.11.2020, Nr. 1, date:12.2020: 1-10
	16406	Use of machine learning to identify novel, behaviorally active antagonists of the insect odorant receptor co-receptor (Orco) subunit Enthalten in Scientific reports Bd. 9, 11.3.2019, Nr. 1, date:12.2019: 1-18
	16407	Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device Enthalten in BMC medical informatics and decision making Bd. 22, 6.7.2022, Nr. 1, date:12.2022: 1-12
	16408	Use of machine learning to improve the estimation of conductivity and permittivity based on longitudinal relaxation time T1 in magnetic resonance at 7 T Enthalten in Scientific reports Bd. 13, 15.5.2023, Nr. 1, date:12.2023: 1-17
	16409	USE OF MULTIVARIATE MACHINE LEARNING ANALYSIS TECHNIQUES FOR FLOOD RISK PREVENTION Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLII-3/W4, 2018: 549-554
	16410	Use of structure-activity landscape index curves and curve integrals to evaluate the performance of multiple machine learning prediction models Enthalten in Journal of cheminformatics Bd. 3, 7.2.2011, Nr. 1, date:12.2011: 1-12