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Ergebnis der Suche nach: "Machine Learning"
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16911 - 16920 von 17232

	16911	Unraveling the significance of cuproptosis in hepatocellular carcinoma heterogeneity and tumor microenvironment through integrated single-cell sequencing and machine learning approaches Enthalten in Discover oncology Bd. 16, 24.5.2025, Nr. 1, date:12.2025: 1-17
	16912	Unravelling individual rhythmic abilities using machine learning Enthalten in Scientific reports Bd. 14, 11.1.2024, Nr. 1, date:12.2024: 1-16
	16913	Unravelling intubation challenges: a machine learning approach incorporating multiple predictive parameters Enthalten in BMC anesthesiology Bd. 24, 18.12.2024, Nr. 1, date:12.2024: 1-14
	16914	Unravelling single-cell DNA replication timing dynamics using machine learning reveals heterogeneity in cancer progression Enthalten in Nature Communications Bd. 16, 8.2.2025, Nr. 1, date:12.2025: 1-15
	16915	Unravelling the human taste receptor interactome: machine learning and molecular modelling insights into protein-protein interactions Enthalten in npj science of food Bd. 9, 1.7.2025, Nr. 1, date:12.2025: 1-16
	16916	Unsupervised Learning and Pattern Recognition of Biological Data Structures with Density Functional Theory and Machine Learning Enthalten in Scientific reports Bd. 8, 11.1.2018, Nr. 1, date:12.2018: 1-11
	16917	Unsupervised machine learning analysis of optical coherence tomography radiomics features for predicting treatment outcomes in diabetic macular edema Enthalten in Scientific reports Bd. 15, 18.4.2025, Nr. 1, date:12.2025: 1-13
	16918	Unsupervised machine learning and cepstral analysis with 4D-STEM for characterizing complex microstructures of metallic alloys Enthalten in npj computational materials Bd. 10, 18.9.2024, Nr. 1, date:12.2024: 1-10
	16919	Unsupervised machine learning and multi-seismic attributes for fault and fracture network interpretation in the Kerry Field, Taranaki Basin, New Zealand Enthalten in Geomechanics and geophysics for geo-energy and geo-resources Bd. 9, 26.9.2023, Nr. 1, date:12.2023: 1-27
	16920	Unsupervised machine learning applied to scanning precession electron diffraction data Enthalten in Advanced structural and chemical imaging Bd. 5, 15.3.2019, Nr. 1, date:12.2019: 1-14

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