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Ergebnis der Suche nach: "Machine Learning"
im Bestand: Gesamter Bestand

36461 - 36470 von 37334

	36461	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
	36462	The Use of Machine Learning in the Analytical Control of the Preparations of Medicinal Plants Enthalten in Inorganic materials Bd. 55, 25.2.2020, Nr. 14, date:12.2019: 1428-1438
	36463	The use of machine learning methods in classification of pumpkin seeds (Cucurbita pepo L.) Enthalten in Genetic resources and crop evolution Bd. 68, 25.6.2021, Nr. 7, date:10.2021: 2713-2726
	36464	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
	36465	The use of machine learning to predict acute hepatopancreatic necrosis disease (AHPND) in shrimp farmed on the east coast of the Mekong Delta of Vietnam Enthalten in Fisheries science Bd. 86, 6.5.2020, Nr. 4, date:7.2020: 673-683
	36466	The use of machine learning to predict the effects of cryoprotective agents on the GelMA-based bioinks used in extrusion cryobioprinting Enthalten in Bio-design and manufacturing Bd. 6, 14.6.2023, Nr. 4, date:7.2023: 464-477
	36467	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
	36468	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
	36469	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
	36470	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

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