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41421 - 41430 von 42178

	41421	TwitterGAN: robust spam detection in twitter using novel generative adversarial networks Enthalten in International journal of information technology Bd. 15, 23.6.2023, Nr. 6, date:8.2023: 3103-3111
	41422	Two Decades of Coastal Development across the Arabian Gulf: Insights from Remote Sensing and Machine Learning Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-G-2025, 2025: 331-338. 8 S.
	41423	Two heads are better than one: current landscape of integrating QSP and machine learning Enthalten in Journal of pharmacokinetics and pharmacodynamics Bd. 49, 1.2.2022, Nr. 1, date:2.2022: 5-18
	41424	Two-Line Element Estimation Using Machine Learning Enthalten in The Journal of the astronautical sciences Bd. 68, 9.2.2021, Nr. 1, date:3.2021: 273-299
	41425	Two machine learning-based nomogram to predict risk and prognostic factors for liver metastasis from pancreatic neuroendocrine tumors: a multicenter study Enthalten in BMC cancer Bd. 23, 9.6.2023, Nr. 1, date:12.2023: 1-18
	41426	Two neuroanatomical subtypes of males with autism spectrum disorder revealed using semi-supervised machine learning Enthalten in Molecular autism Bd. 13, 23.2.2022, Nr. 1, date:12.2022: 1-14
	41427	Two party key exchange protocol based on duo circulant matrices for the IoT environment Enthalten in International journal of information technology Bd. 16, 4.6.2024, Nr. 6, date:8.2024: 3585-3596
	41428	Two-phase Carreau bio-magnetic hybrid nanofluid flow over an inclined spinning disk: numerical simulation and machine learning Enthalten in Multiscale and multidisciplinary modeling, experiments and design Bd. 8, 25.6.2025, Nr. 8, date:8.2025: 1-25
	41429	Two phase feature-ranking for new soil dataset for Coxiella burnetii persistence and classification using machine learning models Enthalten in Scientific reports Bd. 13, 2.1.2023, Nr. 1, date:12.2023: 1-15
	41430	Two-phase flow regime identification based on the liquid-phase velocity information and machine learning Enthalten in Experiments in fluids Bd. 61, 14.9.2020, Nr. 10, date:10.2020: 1-16