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Ergebnis der Suche nach: "Machine Learning"
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16441 - 16450 von 16966

	16441	The use of cloud based machine learning to predict outcome in intracerebral haemorrhage without explicit programming expertise Enthalten in Neurosurgical review Bd. 47, 3.12.2024, Nr. 1, date:12.2024: 1-9
	16442	The Use of Fitness-Fatigue Models for Sport Performance Modelling: Conceptual Issues and Contributions from Machine-Learning Enthalten in Sports medicine - open Bd. 8, 3.3.2022, Nr. 1, date:12.2022: 1-6
	16443	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
	16444	The use of machine learning in rare diseases: a scoping review Enthalten in Orphanet journal of rare diseases Bd. 15, 9.6.2020, Nr. 1, date:12.2020: 1-10
	16445	The use of machine learning modeling, virtual screening, molecular docking, and molecular dynamics simulations to identify potential VEGFR2 kinase inhibitors Enthalten in Scientific reports Bd. 12, 5.11.2022, Nr. 1, date:12.2022: 1-14
	16446	The use of Multispectral Radio-Meter (MSR5) data for wheat crop genotypes identification using machine learning models Enthalten in Scientific reports Bd. 13, 14.11.2023, Nr. 1, date:12.2023: 1-15
	16447	The Utility of Machine Learning Models for Predicting Chemical Contaminants in Drinking Water: Promise, Challenges, and Opportunities Enthalten in Current environmental health reports Bd. 10, 17.12.2022, Nr. 1, date:3.2023: 45-60
	16448	The value of CCTA combined with machine learning for predicting angina pectoris in the anomalous origin of the right coronary artery Enthalten in Biomedical engineering online Bd. 23, 12.9.2024, Nr. 1, date:12.2024: 1-13
	16449	The value of intratumoral and peritumoral ultrasound radiomics model constructed using multiple machine learning algorithms for non-mass breast cancer Enthalten in Scientific reports Bd. 15, 6.6.2025, Nr. 1, date:12.2025: 1-14
	16450	The value of linear and non-linear quantitative EEG analysis in paediatric epilepsy surgery: a machine learning approach Enthalten in Scientific reports Bd. 14, 13.5.2024, Nr. 1, date:12.2024: 1-10

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