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Ergebnis der Suche nach: "Machine Learning"
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41021 - 41030 von 41268

	41021	Utilizing machine learning for flow zone indicators prediction and hydraulic flow unit classification Enthalten in Scientific reports Bd. 14, 20.2.2024, Nr. 1, date:12.2024: 1-29
	41022	Utilizing Machine Learning for Pre- and Postoperative Assessment of Patients Undergoing Resection for BCLC-0, A and B Hepatocellular Carcinoma: Implications for Resection Beyond the BCLC Guidelines Enthalten in Annals of surgical oncology Bd. 27, 6.11.2019, Nr. 3, date:3.2020: 866-874
	41023	Utilizing machine learning models for predicting outcomes in acute pancreatitis: development and validation in three retrospective cohorts Enthalten in BMC medical informatics and decision making Bd. 25, 11.7.2025, Nr. 1, date:12.2025: 1-22
	41024	Utilizing machine learning models to grasp water quality dynamic changes in lake eutrophication through phytoplankton parameters Enthalten in Frontiers of environmental science & engineering Bd. 19, 18.11.2024, Nr. 2, date:2.2025: 1-16
	41025	Utilizing Machine Learning Models with Limited Meteorological Data as Alternatives for the FAO-56PM Model in Estimating Reference Evapotranspiration Enthalten in Water resources management Bd. 38, 7.2.2024, Nr. 6, date:4.2024: 1921-1942
	41026	Utilizing machine learning to analyze trunk movement patterns in women with postpartum low back pain Enthalten in Scientific reports Bd. 14, 12.8.2024, Nr. 1, date:12.2024: 1-24
	41027	Utilizing machine learning to classify persistent organic pollutants in the serum of pregnant women: a predictive modeling approach Enthalten in Environmental science and pollution research Bd. 31, 21.8.2024, Nr. 40, date:8.2024: 52980-52995
	41028	Utilizing machine learning to facilitate the early diagnosis of posterior circulation stroke Enthalten in BMC neurology Bd. 24, 7.5.2024, Nr. 1, date:12.2024: 1-12
	41029	Utilizing machine learning to identify fall predictors in India's aging population: findings from the LASI Enthalten in BMC geriatrics Bd. 25, 17.3.2025, Nr. 1, date:12.2025: 1-11
	41030	Utilizing machine learning to model interdependency of bulk molecular weight, solution concentration, and thickness of spin coated polystyrene thin films Enthalten in Materials Research Society: MRS communications Bd. 14, 12.2.2024, Nr. 2, date:4.2024: 230-236