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32881 - 32890 von 33153

	32881	Utilization of Natural Zeolite (Scolecite) to Reduce Arsenic Contamination of Water in Relation to Machine Learning Approach Enthalten in Water, air & soil pollution Bd. 235, 5.2.2024, Nr. 2, date:2.2024: 1-17
	32882	Utilization of non-invasive ventilation before prehospital emergency anesthesia in trauma – a cohort analysis with machine learning Enthalten in Scandinavian journal of trauma, resuscitation and emergency medicine Bd. 33, 3.3.2025, Nr. 1, date:12.2025: 1-14
	32883	Utilization of sequential model-based optimizer integrated machine learning models in correlation of famotidine solubility in supercritical carbon dioxide Enthalten in Scientific reports Bd. 15, 10.10.2025, Nr. 1, date:12.2025: 1-14
	32884	Utilization of tree-based machine learning models for predicting low birth weight cases Enthalten in BMC pregnancy and childbirth Bd. 25, 26.2.2025, Nr. 1, date:12.2025: 1-32
	32885	Utilizing a fusion of remote sensing data and machine learning models to forecast flood risks to agriculture in Hanoi City, Vietnam Enthalten in Letters in spatial and resource sciences Bd. 17, 24.6.2024, Nr. 1, date:12.2024: 1-19
	32886	Utilizing a publicly accessible automated machine learning platform to enable diagnosis before tumor surgery Enthalten in Communications medicine Bd. 5, 8.10.2025, Nr. 1, date:12.2025: 1-7
	32887	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
	32888	Utilizing decision tree machine learning model to map dental students’ preferred learning styles with suitable instructional strategies Enthalten in BMC medical education Bd. 24, 11.1.2024, Nr. 1, date:12.2024: 1-13
	32889	Utilizing graph Fourier transform for automatic Alzheimer’s disease detection from EEG signals Enthalten in International journal of information technology Bd. 16, 27.1.2024, Nr. 3, date:3.2024: 1653-1659
	32890	Utilizing integrated bioinformatics and machine learning approaches to elucidate biomarkers linking sepsis to fatty acid metabolism-associated genes Enthalten in Scientific reports Bd. 14, 22.11.2024, Nr. 1, date:12.2024: 1-15

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