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Ergebnis der Suche nach:
"Machine Learning"
im Bestand: Gesamter Bestand
38611 - 38620 von 38861
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Titel (A-Z)
Titel (Z-A)
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Name (Z-A)
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38611
Utility of pre-treatment FDG PET/CT–derived machine learning models for outcome prediction in classical Hodgkin lymphoma
Enthalten in European radiology Bd. 32, 25.8.2022, Nr. 10, date:10.2022: 7237-7247
38612
Utilization of artificial intelligence and machine learning in chemistry education: a critical review
Enthalten in Discover education Bd. 3, 10.7.2024, Nr. 1, date:12.2024: 1-15
38613
Utilization of machine learning algorithm in the prediction of rehospitalization during one-year post traumatic spinal cord injury
Enthalten in Spinal cord Bd. 63, 15.2.2025, Nr. 4, date:4.2025: 214-221
38614
Utilization of machine learning algorithms for forecasting the likelihood of liquefaction potential in geotechnical layers of Tabriz City
Enthalten in Bulletin of engineering geology and the environment Bd. 84, 15.5.2025, Nr. 6, date:6.2025: 1-30
38615
Utilization of machine learning approach for production of optimized PLGA nanoparticles for drug delivery applications
Enthalten in Scientific reports Bd. 15, 14.3.2025, Nr. 1, date:12.2025: 1-14
38616
Utilization of machine learning for dengue case screening
Enthalten in BMC public health Bd. 24, 11.6.2024, Nr. 1, date:12.2024: 1-9
38617
Utilization of machine learning for the estimation of production rates in wells operated by electrical submersible pumps
Enthalten in Journal of petroleum exploration and production technology Bd. 14, 22.2.2024, Nr. 5, date:5.2024: 1205-1233
38618
Utilization of machine learning models in predicting caries risk groups and oral health-related risk factors in adults
Enthalten in BMC oral health Bd. 24, 8.4.2024, Nr. 1, date:12.2024: 1-19
38619
Utilization of machine learning to test the impact of cognitive processing and emotion recognition on the development of PTSD following trauma exposure
Enthalten in BMC psychiatry Bd. 20, 1.7.2020, Nr. 1, date:12.2020: 1-11
38620
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
38611 - 38620 von 38861
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