Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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43271 - 43280 von 43747

	43271	Usefulness of machine learning softwares to screen titles of systematic reviews: a methodological study Enthalten in Systematic Reviews Bd. 12, 15.4.2023, Nr. 1, date:12.2023: 1-14
	43272	User structural information in priority-based ranking for top-N recommendation Enthalten in Advances in computational intelligence Bd. 3, 6.1.2023, Nr. 1, date:2.2023: 1-16
	43273	User training for machine learning controlled upper limb prostheses: a serious game approach Enthalten in Journal of neuroEngineering and rehabilitation Bd. 18, 12.2.2021, Nr. 1, date:12.2021: 1-15
	43274	Using a cohort study of diabetes and peripheral artery disease to compare logistic regression and machine learning via random forest modeling Enthalten in BMC medical research methodology Bd. 22, 23.11.2022, Nr. 1, date:12.2022: 1-10
	43275	Using a machine learning approach to identify key prognostic molecules for esophageal squamous cell carcinoma Enthalten in BMC cancer Bd. 21, 9.8.2021, Nr. 1, date:12.2021: 1-11
	43276	Using a Machine Learning Methodology to Analyze Reddit Posts regarding Child Feeding Information Enthalten in Journal of child and family studies Bd. 30, 27.2.2021, Nr. 5, date:5.2021: 1290-1298
	43277	Using a multi-staged strategy based on machine learning and mathematical modeling to predict genotype-phenotype risk patterns in diabetic kidney disease: a prospective case–control cohort analysis Enthalten in BMC nephrology Bd. 14, 23.7.2013, Nr. 1, date:12.2013: 1-9
	43278	Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches Enthalten in BMC medical informatics and decision making Bd. 25, 31.1.2025, Nr. 1, date:12.2025: 1-10
	43279	Using a Sociotechnical Model to Understand Challenges with Sepsis Recognition among Critically Ill Infants Enthalten in ACI Open Bd. 06, 2022, Nr. 02: e57-e65
	43280	Using acoustic emission signal analysis and machine learning algorithms for predicting mechanical hardness in laser directed energy deposition parts Enthalten in The international journal of advanced manufacturing technology Bd. 138, 28.5.2025, Nr. 9-10, date:6.2025: 4455-4474

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