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Ergebnis der Suche nach: "Machine Learning"
im Bestand: Gesamter Bestand

41861 - 41870 von 42102
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Artikel 41861 Utilizing machine learning to predict participant response to follow-up health surveys in the Millennium Cohort Study
Enthalten in Scientific reports Bd. 14, 28.10.2024, Nr. 1, date:12.2024: 1-12
Online Ressource
Artikel 41862 Utilizing machine learning to predict post-treatment outcomes in chronic non-specific neck pain patients undergoing cervical extension traction
Enthalten in Scientific reports Bd. 14, 23.5.2024, Nr. 1, date:12.2024: 1-13
Online Ressource
Artikel 41863 Utilizing Ni(II) complex for metal drug-gel particles in cervical cancer treatment and designing novel drugs through machine learning methods
Enthalten in Scientific reports Bd. 14, 5.3.2024, Nr. 1, date:12.2024: 1-9
Online Ressource
Artikel 41864 Utilizing reinforcement learning for de novo drug design
Enthalten in Machine learning Bd. 113, 8.4.2024, Nr. 7, date:7.2024: 4811-4843
Online Ressource
Artikel 41865 Utilizing SMOTE-TomekLink and machine learning to construct a predictive model for elderly medical and daily care services demand
Enthalten in Scientific reports Bd. 15, 11.3.2025, Nr. 1, date:12.2025: 1-12
Online Ressource
Artikel 41866 Utilizing social media and machine learning for personality and emotion recognition using PERS
Enthalten in Neural computing & applications Bd. 35, 5.9.2023, Nr. 33, date:11.2023: 23927-23941
Online Ressource
Artikel 41867 Utilizing Supervised Machine Learning and Technical Indicators for Quantitative Trading to Improve Stock Market Trading Decisions
Enthalten in SN Computer Science Bd. 6, 26.5.2025, Nr. 5, date:6.2025: 1-17
Online Ressource
Artikel 41868 Utilizing the concept of risk in calibrating the vulnerability of coastal-alluvial aquifers based on machine learning methods
Enthalten in International journal of environmental science and technology Bd. 22, 5.9.2025, Nr. 16, date:12.2025: 16747-16762
Online Ressource
Artikel 41869 UWB anchor nodes self-calibration in NLOS conditions: a machine learning and adaptive PHY error correction approach
Enthalten in Wireless networks Bd. 27, 7.5.2021, Nr. 4, date:5.2021: 3007-3023
Online Ressource
Artikel 41870 VacPred: Sequence-based prediction of plant vacuole proteins using machine-learning techniques
Enthalten in Journal of biosciences Bd. 45, 27.8.2020, Nr. 1, date:12.2020: 1-9
Online Ressource


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