Katalog der Deutschen Nationalbibliothek

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

38491 - 38500 von 38842

	38491	Using machine learning to determine the correlation between physiological and environmental parameters and the induction of acute mountain sickness Enthalten in BMC bioinformatics Bd. 22, 31.5.2022, Nr. 5, date:11.2021: 1-14
	38492	Using machine learning to determine the time of exposure to infection by a respiratory pathogen Enthalten in Scientific reports Bd. 13, 1.4.2023, Nr. 1, date:12.2023: 1-10
	38493	Using machine learning to develop a clinical prediction model for SSRI-associated bleeding: a feasibility study Enthalten in BMC medical informatics and decision making Bd. 23, 11.6.2023, Nr. 1, date:12.2023: 1-11
	38494	Using machine learning to develop a five-item short form of the children’s depression inventory Enthalten in BMC public health Bd. 24, 23.4.2024, Nr. 1, date:12.2024: 1-11
	38495	Using machine learning to develop a stacking ensemble learning model for the CT radiomics classification of brain metastases Enthalten in Scientific reports Bd. 14, 19.11.2024, Nr. 1, date:12.2024: 1-11
	38496	Using machine learning to discover DNA metabolism biomarkers that direct prostate cancer treatment Enthalten in Scientific reports Bd. 15, 18.7.2025, Nr. 1, date:12.2025: 1-18
	38497	Using Machine Learning to Establish Predictors of Mortality in Patients Undergoing Laparotomy for Emergency General Surgical Conditions Enthalten in World journal of surgery Bd. 46, 26.10.2021, Nr. 2, date:2.2022: 339-346
	38498	Using machine learning to estimate the incidence rate of intimate partner violence Enthalten in Scientific reports Bd. 13, 4.4.2023, Nr. 1, date:12.2023: 1-9
	38499	Using machine learning to examine the relationship between asthma and absenteeism Enthalten in Environmental monitoring and assessment Bd. 191, 28.6.2019, Nr. 2, date:6.2019: 1-9
	38500	Using machine learning to explore core risk factors associated with the risk of eating disorders among non-clinical young women in China: A decision-tree classification analysis Enthalten in Journal of eating disorders Bd. 10, 10.2.2022, Nr. 1, date:12.2022: 1-11