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Ergebnis der Suche nach: "Machine Learning"
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16751 - 16760 von 17051

	16751	Unsupervised machine-learning method for improving the performance of ambulatory fall-detection systems Enthalten in Biomedical engineering online Bd. 11, 16.2.2012, Nr. 1, date:12.2012: 1-11
	16752	Unsupervised machine learning method for indirect estimation of reference intervals for chronic kidney disease in the Puerto Rican population Enthalten in Scientific reports Bd. 13, 11.10.2023, Nr. 1, date:12.2023: 1-11
	16753	Unsupervised Machine Learning Revealed that Repeat Transcranial Magnetic Stimulation is More Suitable for Stroke Patients with Statin Enthalten in Neurology and Therapy Bd. 13, 30.4.2024, Nr. 3, date:6.2024: 857-868
	16754	Unsupervised machine learning to investigate trajectory patterns of COVID-19 symptoms and physical activity measured via the MyHeart Counts App and smart devices Enthalten in npj digital medicine Bd. 6, 22.12.2023, Nr. 1, date:12.2023: 1-11
	16755	UNSUPERVISED METHODOLOGY TO IN-SEASON MAPPING OF SUMMER CROPS IN URUGUAY WITH MODIS EVI’S TEMPORAL SERIES AND MACHINE LEARNING Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLII-3/W12-2020, 2020: 171-176
	16756	Unveiling Adolescent Suicidality: Holistic Analysis of Protective and Risk Factors Using Multiple Machine Learning Algorithms Enthalten in Journal of youth and adolescence Bd. 53, 20.11.2023, Nr. 3, date:3.2024: 507-525
	16757	Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach Enthalten in Scientific reports Bd. 15, 26.4.2025, Nr. 1, date:12.2025: 1-18
	16758	Unveiling degradation patterns in dye-sensitized solar cells: a machine learning perspective Enthalten in Scientific reports Bd. 15, 3.7.2025, Nr. 1, date:12.2025: 1-14
	16759	Unveiling hydrogen chemical states in supersaturated amorphous alumina via machine learning-driven atomistic modeling Enthalten in npj computational materials Bd. 11, 6.6.2025, Nr. 1, date:12.2025: 1-13
	16760	Unveiling lipoprotein subfractions signature in high-FNPO PCOS: implications for PCOM diagnosis and risk assessment using advanced machine learning models Enthalten in BMC medicine Bd. 23, 19.5.2025, Nr. 1, date:12.2025: 1-12

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