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27071 - 27080 von 32527

	27071	Methodological guidelines to estimate population-based health indicators using linked data and/or machine learning techniques Enthalten in Archives of public health Bd. 80, 4.1.2022, Nr. 1, date:12.2022: 1-12
	27072	Methodological Techniques Used in Machine Learning to Support Individualized Drug Dosing Regimens Based on Pharmacokinetic Data: A Scoping Review Enthalten in Clinical pharmacokinetics Bd. 64, 14.8.2025, Nr. 9, date:9.2025: 1295-1330
	27073	Methodology and evaluation in sports analytics: challenges, approaches, and lessons learned Enthalten in Machine learning Bd. 113, 17.7.2024, Nr. 9, date:9.2024: 6977-7010
	27074	Methodology for biomarker discovery with reproducibility in microbiome data using machine learning Enthalten in BMC bioinformatics Bd. 25, 15.1.2024, Nr. 1, date:12.2024: 1-17
	27075	Methodology for contamination detection and reduction in fermentation processes using machine learning Enthalten in Bioprocess and biosystems engineering Bd. 48, 26.6.2025, Nr. 9, date:9.2025: 1547-1563
	27076	Methodology For Extracting Poplar Planted Fields From Very High-Resolution Imagery Using Object-Based Image Analysis and Feature Selection Strategy Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. X-5-2024, 2024: 259-265. 7 S.
	27077	Methodology for the Characterisation of Linear Rail Transport Infrastructures with the Machine Learning Technique and Their Application in a Hyperloop Network Enthalten in Urban rail transit Bd. 7, 20.5.2021, Nr. 3, date:9.2021: 159-176
	27078	Methodology of Mediametric Information Analysis with the Use of Machine Learning Algorithms Enthalten in Automatic control and computer sciences Bd. 55, 1.3.2022, Nr. 8, date:12.2021: 970-977
	27079	Methodology of the quantitative assessment of the moisture content of saline brick walls in historic buildings using machine learning Enthalten in Archives of civil and mechanical engineering Bd. 23, 12.5.2023, Nr. 3, date:8.2023: 1-15
	27080	Methods and applications of machine learning in computational design of optoelectronic semiconductors Enthalten in Science China materials Bd. 67, 19.3.2024, Nr. 4, date:4.2024: 1042-1081

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