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27751 |
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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27752 |
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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27753 |
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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27754 |
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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27755 |
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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27756 |
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
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27757 |
Using algorithmic game theory to improve supervised machine learning: A novel applicability approach in flood susceptibility mapping
Enthalten in Environmental science and pollution research Bd. 31, 19.8.2024, Nr. 40, date:8.2024: 52740-52757
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27758 |
Using an adaptive network-based fuzzy inference system for prediction of successful aging: a comparison with common machine learning algorithms
Enthalten in BMC medical informatics and decision making Bd. 23, 19.10.2023, Nr. 1, date:12.2023: 1-14
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27759 |
Using an ensemble machine learning model to delineate groundwater potential zones in desert fringes of East Esna-Idfu area, Nile valley, Upper Egypt
Enthalten in Geoscience Letters Bd. 10, 9.2.2023, Nr. 1, date:12.2023: 1-19
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27760 |
Using Artificial Intelligence and Machine Learning for Rapidly Identifying Manufacturing Failures
Enthalten in Journal of failure analysis and prevention Bd. 22, 14.10.2022, Nr. 5, date:10.2022: 1813-1815
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