Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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32901 - 32910 von 33402

	32901	Use of machine learning algorithms to construct models of symptom burden cluster risk in breast cancer patients undergoing chemotherapy Enthalten in Supportive care in cancer Bd. 33, 13.2.2025, Nr. 3, date:3.2025: 1-10
	32902	Use of Machine Learning Approaches in Clinical Epidemiological Research of Diabetes Enthalten in Current diabetes reports Bd. 20, 3.12.2020, Nr. 12, date:12.2020: 1-19
	32903	Use of machine learning-based classification algorithms in the monitoring of Land Use and Land Cover practices in a hilly terrain Enthalten in Environmental monitoring and assessment Bd. 196, 5.12.2023, Nr. 1, date:1.2024: 1-21
	32904	Use of machine learning-based integration to develop a monocyte differentiation-related signature for improving prognosis in patients with sepsis Enthalten in Molecular medicine Bd. 29, 20.3.2023, Nr. 1, date:12.2023: 1-16
	32905	Use of Machine Learning for Dosage Individualization of Vancomycin in Neonates Enthalten in Clinical pharmacokinetics Bd. 62, 10.6.2023, Nr. 8, date:8.2023: 1105-1116
	32906	Use of machine learning for risk stratification of chest pain patients in the emergency department Enthalten in BMC medical informatics and decision making Bd. 25, 24.10.2025, Nr. 1, date:12.2025: 1-12
	32907	Use of machine learning in the financial sector: an analysis of trends and the research agenda Enthalten in Discover artificial intelligence Bd. 5, 22.10.2025, Nr. 1, date:12.2025: 1-31
	32908	Use of Machine Learning Methods to Analyze Patterns of Brain Activity during Assessment of the Self and Others Enthalten in Neuroscience and behavioral physiology Bd. 53, 25.11.2023, Nr. 7, date:9.2023: 1210-1218
	32909	Use of Machine Learning Models for Classification of Myographic Diseases Enthalten in Biomedical engineering Bd. 56, 12.1.2023, Nr. 5, date:1.2023: 353-357
	32910	Use of machine learning models for prediction of compressive strength of concrete produced with waste materials Enthalten in Innovative infrastructure solutions Bd. 10, 12.9.2025, Nr. 10, date:10.2025: 1-29

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