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Ergebnis der Suche nach: "Machine Learning"
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34571 - 34580 von 37178

	34571	Proposing an ensemble machine learning based drought vulnerability index using M5P, dagging, random sub-space and rotation forest models Enthalten in Stochastic environmental research and risk assessment Bd. 37, 6.3.2023, Nr. 7, date:7.2023: 2513-2540
	34572	Prospective prediction of PTSD diagnosis in a nationally representative sample using machine learning Enthalten in BMC psychiatry Bd. 20, 10.11.2020, Nr. 1, date:12.2020: 1-10
	34573	Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis Enthalten in Nature medicine Bd. 28, 21.7.2022, Nr. 7, date:7.2022: 1455-1460
	34574	Prospects of non-resonant di-Higgs searches and Higgs boson self-coupling measurement at the HE-LHC using machine learning techniques Enthalten in Journal of high energy physics Bd. 2020, 28.12.2020, Nr. 12, date:12.2020: 1-47
	34575	PrOsteoporosis: predicting osteoporosis risk using NHANES data and machine learning approach Enthalten in Biomed Central (London): BMC Research Notes Bd. 18, 11.3.2025, Nr. 1, date:12.2025: 1-10
	34576	Protecting Machine Learning Models from Training Data Set Extraction Enthalten in Automatic control and computer sciences Bd. 58, 14.3.2025, Nr. 8, date:12.2024: 1234-1241
	34577	Protection against Adversarial Attacks on Malware Detectors Using Machine Learning Algorithms Enthalten in Automatic control and computer sciences Bd. 55, 1.3.2022, Nr. 8, date:12.2021: 1025-1028
	34578	Protection of Computational Machine Learning Models against Extraction Threat Enthalten in Automatic control and computer sciences Bd. 57, 29.2.2024, Nr. 8, date:12.2023: 996-1004
	34579	Protein data in the identification and stage prediction of bronchopulmonary dysplasia on preterm infants: a machine learning study Enthalten in International journal of information technology Bd. 16, 29.11.2023, Nr. 1, date:1.2024: 387-392
	34580	Protein interactions, network pharmacology, and machine learning work together to predict genes linked to mitochondrial dysfunction in hypertrophic cardiomyopathy Enthalten in Scientific reports Bd. 15, 29.4.2025, Nr. 1, date:12.2025: 1-23

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