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25911 |
Predicting the propensity for thermally activated β events in metallic glasses via interpretable machine learning
Enthalten in npj computational materials Bd. 6, 15.12.2020, Nr. 1, date:12.2020: 1-12
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25912 |
Predicting the pulse of urban water demand: a machine learning approach to deciphering meteorological influences
Enthalten in Biomed Central (London): BMC Research Notes Bd. 17, 9.8.2024, Nr. 1, date:12.2024: 1-6
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25913 |
Predicting the Recurrence of Common Bile Duct Stones After ERCP Treatment with Automated Machine Learning Algorithms
Enthalten in Digestive diseases and sciences Bd. 68, 9.5.2023, Nr. 7, date:7.2023: 2866-2877
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25914 |
Predicting the risk category of thymoma with machine learning-based computed tomography radiomics signatures and their between-imaging phase differences
Enthalten in Scientific reports Bd. 14, 19.8.2024, Nr. 1, date:12.2024: 1-12
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25915 |
Predicting the risk of diabetes complications using machine learning and social administrative data in a country with ethnic inequities in health: Aotearoa New Zealand
Enthalten in BMC medical informatics and decision making Bd. 24, 27.9.2024, Nr. 1, date:12.2024: 1-13
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25916 |
Predicting the risk of ibrutinib in combination with R-ICE in patients with relapsed or refractory DLBCL using explainable machine learning algorithms
Enthalten in Clinical and experimental medicine Bd. 25, 26.5.2025, Nr. 1, date:12.2025: 1-12
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25917 |
Predicting the risk of inappropriate depth of endotracheal intubation in pediatric patients using machine learning approaches
Enthalten in Scientific reports Bd. 13, 29.3.2023, Nr. 1, date:12.2023: 1-9
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25918 |
Predicting the Risk of Lumbar Prolapsed Disc: A Gene Signature-Based Machine Learning Analysis
Enthalten in Pain and therapy Bd. 14, 4.5.2025, Nr. 3, date:6.2025: 1117-1129
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25919 |
Predicting the risk of osteoporosis in older Vietnamese women using machine learning approaches
Enthalten in Scientific reports Bd. 12, 23.11.2022, Nr. 1, date:12.2022: 1-17
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25920 |
Predicting the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms
Enthalten in European journal of medical research Bd. 29, 23.12.2024, Nr. 1, date:12.2024: 1-9
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Administration
