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	511	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
	512	Using machine learning techniques for rationalising phenotypic readouts from a rat sleeping model Enthalten in Journal of cheminformatics Bd. 5, 22.3.2013, Nr. 1, date:3.2013: 1
	513	Using Machine Learning techniques in phenomenological studies on flavour physics Enthalten in Journal of high energy physics Bd. 2022, 19.7.2022, Nr. 7, date:7.2022: 1-43
	514	USING MACHINE LEARNING TECHNIQUES TO FILTER VEGETATION IN COLORIZED SFM POINT CLOUDS OF SOIL SURFACES Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-1/W2-2023, 2023: 163-170. 8 S.
	515	Using machine learning techniques to predict the cost of repairing hard failures in underground fiber optics networks Enthalten in Journal of Big Data Bd. 7, 24.8.2020, Nr. 1, date:12.2020: 1-16
	516	Using machine learning techniques to predict the risk of osteoporosis based on nationwide chronic disease data Enthalten in Scientific reports Bd. 14, 4.3.2024, Nr. 1, date:12.2024: 1-11
	517	Using transfer learning and dimensionality reduction techniques to improve generalisability of machine-learning predictions of mosquito ages from mid-infrared spectra Enthalten in BMC bioinformatics Bd. 24, 9.1.2023, Nr. 1, date:12.2023: 1-15
	518	Utilizing contemporary machine learning techniques for determining soilcrete properties Enthalten in Earth science informatics Bd. 18, 14.1.2025, Nr. 1, date:1.2025: 1-30
	519	Utilizing genomic signatures to gain insights into the dynamics of SARS-CoV-2 through Machine and Deep Learning techniques Enthalten in BMC bioinformatics Bd. 25, 27.3.2024, Nr. 1, date:12.2024: 1-17
	520	Various optimized machine learning techniques to predict agricultural commodity prices Enthalten in Neural computing & applications Bd. 36, 16.4.2024, Nr. 19, date:7.2024: 11439-11459

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