Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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20181 - 20190 von 20215

	20181	Which are best for successful aging prediction? Bagging, boosting, or simple machine learning algorithms? Enthalten in Biomedical engineering online Bd. 22, 29.8.2023, Nr. 1, date:12.2023: 1-25
	20182	Which insulin resistance indices best predict future frailty progression in a cardiovascular-kidney-metabolic syndrome stage 0–3 population: a national prospective cohort and machine learning study Enthalten in Diabetology & metabolic syndrome Bd. 17, 13.11.2025, Nr. 1, date:12.2025: 1-16
	20183	Which surrogate insulin resistance indices best predict coronary artery disease? A machine learning approach Enthalten in Cardiovascular diabetology Bd. 23, 21.6.2024, Nr. 1, date:12.2024: 1-13
	20184	Whole-orbit radiomics: machine learning-based multi- and fused- region radiomics signatures for intravenous glucocorticoid response prediction in thyroid eye disease Enthalten in Journal of translational medicine Bd. 22, 13.1.2024, Nr. 1, date:12.2024: 1-14
	20185	Why and how to construct an epistemic justification of machine learning? Enthalten in Synthese Bd. 204, 10.8.2024, Nr. 2, date:8.2024: 1-24
	20186	Why did individuals seeking COVID-19 advice return to internet hospitals for follow-up in the early pandemic: Insights from machine learning Enthalten in BMC public health Bd. 25, 10.11.2025, Nr. 1, date:12.2025: 1-16
	20187	Why does machine learning work really well in many engineering problems? Enthalten in Machine learning for computational science and engineering Bd. 1, 20.8.2025, Nr. 2, date:12.2025: 1-13
	20188	Wide dynamic range and real-time reagent identification and imaging using multi-wavelength terahertz parametric generation and machine learning Enthalten in Scientific reports Bd. 13, 7.8.2023, Nr. 1, date:12.2023: 1-8
	20189	Wildfire assessment using machine learning algorithms in different regions Enthalten in Fire ecology Bd. 20, 3.12.2024, Nr. 1, date:12.2024: 1-20
	20190	Wildfire Susceptibility Mapping in Karabuk Province, Türkiye Using Machine Learning Algorithms Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-4/W18-2025, 2026: 1-5. 5 S.