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41531 - 41540 von 42121

	41531	Unsupervised machine learning approach to interpret complex lower urinary tract symptoms and their impact on quality of life in adult women Enthalten in World journal of urology Bd. 43, 4.8.2025, Nr. 1, date:12.2025: 1-8
	41532	Unsupervised machine learning approaches to the q-state Potts model Enthalten in The European physical journal / B / Condensed matter and complex systems Bd. 95, 12.11.2022, Nr. 11, date:11.2022: 1-12
	41533	Unsupervised Machine Learning-Based Intrusion Detection in PROFINET Networks Enthalten in Journal of control, automation and electrical systems Bd. 36, 14.6.2025, Nr. 4, date:8.2025: 766-777
	41534	Unsupervised machine learning-based multi-attributes analysis for enhancing gas channel detection and facies classification in the serpent field, offshore Nile Delta, Egypt Enthalten in Geomechanics and geophysics for geo-energy and geo-resources Bd. 10, 28.11.2024, Nr. 1, date:12.2024: 1-22
	41535	Unsupervised machine learning based on clinical factors for the detection of coronary artery atherosclerosis in type 2 diabetes mellitus Enthalten in Cardiovascular diabetology Bd. 21, 28.11.2022, Nr. 1, date:12.2022: 1-10
	41536	Unsupervised machine learning-based stratification and immune deconvolution of liver hepatocellular carcinoma Enthalten in BMC cancer Bd. 25, 10.5.2025, Nr. 1, date:12.2025: 1-16
	41537	Unsupervised machine learning clustering approach for hospitalized COVID-19 pneumonia patients Enthalten in BMC pulmonary medicine Bd. 25, 8.2.2025, Nr. 1, date:12.2025: 1-9
	41538	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
	41539	Unsupervised machine learning for automated corrosion staging using optical microscopy images Enthalten in npj Materials degradation Bd. 9, 8.7.2025, Nr. 1, date:12.2025: 1-9
	41540	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