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Ergebnis der Suche nach: "Machine Learning"
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16661 - 16670 von 16964

	16661	Unsupervised machine learning combined with 4D scanning transmission electron microscopy for bimodal nanostructural analysis Enthalten in Scientific reports Bd. 14, 5.2.2024, Nr. 1, date:12.2024: 1-10
	16662	Unsupervised machine learning for clustering forward head posture, protraction and retraction movement patterns based on craniocervical angle data in individuals with nonspecific neck pain Enthalten in BMC musculoskeletal disorders Bd. 25, 13.5.2024, Nr. 1, date:12.2024: 1-10
	16663	Unsupervised machine learning for disease prediction: a comparative performance analysis using multiple datasets Enthalten in Health and Technology Bd. 14, 29.12.2023, Nr. 1, date:1.2024: 141-154
	16664	Unsupervised machine learning for local stress identification in fatigue analysis of welded joints Enthalten in Welding in the world Bd. 69, 19.11.2024, Nr. 1, date:1.2025: 213-226
	16665	Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data Enthalten in Acta Neuropathologica Communications Bd. 11, 21.12.2023, Nr. 1, date:12.2023: 1-20
	16666	Unsupervised machine learning identifies distinct phenotypes in cardiac complications of pediatric patients treated with anthracyclines Enthalten in Cardio-Oncology Bd. 10, 28.10.2024, Nr. 1, date:12.2024: 1-11
	16667	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
	16668	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
	16669	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
	16670	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

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