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Ergebnis der Suche nach: "Machine Learning"
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27751 - 27760 von 28160
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Artikel 27751 Usefulness of machine learning softwares to screen titles of systematic reviews: a methodological study
Enthalten in Systematic Reviews Bd. 12, 15.4.2023, Nr. 1, date:12.2023: 1-14
Online Ressource
Artikel 27752 User structural information in priority-based ranking for top-N recommendation
Enthalten in Advances in computational intelligence Bd. 3, 6.1.2023, Nr. 1, date:2.2023: 1-16
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Artikel 27753 User training for machine learning controlled upper limb prostheses: a serious game approach
Enthalten in Journal of neuroEngineering and rehabilitation Bd. 18, 12.2.2021, Nr. 1, date:12.2021: 1-15
Online Ressource
Artikel 27754 Using a cohort study of diabetes and peripheral artery disease to compare logistic regression and machine learning via random forest modeling
Enthalten in BMC medical research methodology Bd. 22, 23.11.2022, Nr. 1, date:12.2022: 1-10
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Artikel 27755 Using a machine learning approach to identify key prognostic molecules for esophageal squamous cell carcinoma
Enthalten in BMC cancer Bd. 21, 9.8.2021, Nr. 1, date:12.2021: 1-11
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Artikel 27756 Using a Machine Learning Methodology to Analyze Reddit Posts regarding Child Feeding Information
Enthalten in Journal of child and family studies Bd. 30, 27.2.2021, Nr. 5, date:5.2021: 1290-1298
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Artikel 27757 Using a multi-staged strategy based on machine learning and mathematical modeling to predict genotype-phenotype risk patterns in diabetic kidney disease: a prospective case–control cohort analysis
Enthalten in BMC nephrology Bd. 14, 23.7.2013, Nr. 1, date:12.2013: 1-9
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Artikel 27758 Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches
Enthalten in BMC medical informatics and decision making Bd. 25, 31.1.2025, Nr. 1, date:12.2025: 1-10
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Artikel 27759 Using a Sociotechnical Model to Understand Challenges with Sepsis Recognition among Critically Ill Infants
Enthalten in ACI Open Bd. 06, 2022, Nr. 02: e57-e65
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Artikel 27760 Using alcohol consumption diary data from an internet intervention for outcome and predictive modeling: a validation and machine learning study
Enthalten in BMC medical research methodology Bd. 20, 11.5.2020, Nr. 1, date:12.2020: 1-9
Online Ressource


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