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	601	The effectiveness of data pre-processing methods on the performance of machine learning techniques using RF, SVR, Cubist and SGB: a study on undrained shear strength prediction Enthalten in Stochastic environmental research and risk assessment Bd. 38, 13.6.2024, Nr. 8, date:8.2024: 3273-3290
	602	The use of machine learning and deep learning techniques to assess proprioceptive impairments of the upper limb after stroke Enthalten in Journal of neuroEngineering and rehabilitation Bd. 20, 27.1.2023, Nr. 1, date:12.2023: 1-18
	603	Thermal maturity and TOC prediction using machine learning techniques: case study from the Cretaceous–Paleocene source rock, Taranaki Basin, New Zealand Enthalten in Journal of petroleum exploration and production technology Bd. 10, 14.5.2020, Nr. 6, date:8.2020: 2175-2193
	604	Tongue image fusion and analysis of thermal and visible images in diabetes mellitus using machine learning techniques Enthalten in Scientific reports Bd. 14, 24.6.2024, Nr. 1, date:12.2024: 1-17
	605	TOWARDS MORE RESILIENT SMART CITIES: MT-InSAR MONITORING OF URBAN INFRASTRUCTURE USING MACHINE LEARNING TECHNIQUES Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. X-4/W3-2022, 2022: 221-228. 8 S.
	606	Unified mRNA Subcellular Localization Predictor based on machine learning techniques Enthalten in BMC genomics Bd. 25, 7.2.2024, Nr. 1, date:12.2024: 1-18
	607	Unraveling the mechanisms underlying drug-induced cholestatic liver injury: identifying key genes using machine learning techniques on human in vitro data sets Enthalten in Archives of toxicology Bd. 97, 21.8.2023, Nr. 11, date:11.2023: 2969-2981
	608	Use of machine learning techniques for identifying ischemic stroke instead of the rule-based methods: a nationwide population-based study Enthalten in European journal of medical research Bd. 29, 3.1.2024, Nr. 1, date:12.2024: 1-9
	609	Use of machine learning techniques to identify HIV predictors for screening in sub-Saharan Africa Enthalten in BMC medical research methodology Bd. 21, 31.7.2021, Nr. 1, date:12.2021: 1-11
	610	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

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