Katalog der Deutschen Nationalbibliothek

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

34621 - 34630 von 36581

	34621	Risk factors and predictive models for post-operative moderate-to-severe mitral regurgitation following transcatheter aortic valve replacement: a machine learning approach Enthalten in BMC cardiovascular disorders Bd. 25, 10.5.2025, Nr. 1, date:12.2025: 1-12
	34622	Risk factors and socio-economic burden in pancreatic ductal adenocarcinoma operation: a machine learning based analysis Enthalten in BMC cancer Bd. 20, 27.11.2020, Nr. 1, date:12.2020: 1-12
	34623	Risk Factors Associated with COVID-19 Lethality: A Machine Learning Approach Using Mexico Database Enthalten in Journal of medical systems Bd. 47, 19.8.2023, Nr. 1, date:12.2023: 1-11
	34624	Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse Enthalten in Intensive Care Medicine Experimental Bd. 9, 28.6.2021, Nr. 1, date:12.2021: 1-15
	34625	Risk factors for cardiovascular disease in patients with metabolic-associated fatty liver disease: a machine learning approach Enthalten in Cardiovascular diabetology Bd. 21, 12.11.2022, Nr. 1, date:12.2022: 1-12
	34626	Risk factors for the time to development of retinopathy of prematurity in premature infants in Iran: a machine learning approach Enthalten in BMC ophthalmology Bd. 24, 23.8.2024, Nr. 1, date:12.2024: 1-16
	34627	Risk of bias of prognostic models developed using machine learning: a systematic review in oncology Enthalten in Diagnostic and prognostic research Bd. 6, 7.7.2022, Nr. 1, date:12.2022: 1-14
	34628	Risk prediction for delayed clearance of high-dose methotrexate in pediatric hematological malignancies by machine learning Enthalten in International journal of hematology Bd. 114, 25.6.2021, Nr. 4, date:10.2021: 483-493
	34629	Risk prediction for malignant intraductal papillary mucinous neoplasm of the pancreas: logistic regression versus machine learning Enthalten in Scientific reports Bd. 10, 18.11.2020, Nr. 1, date:12.2020: 1-8
	34630	Risk prediction of 30-day mortality after stroke using machine learning: a nationwide registry-based cohort study Enthalten in BMC neurology Bd. 22, 27.5.2022, Nr. 1, date:12.2022: 1-9