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10911 |
Predicting home delivery and identifying its determinants among women aged 15–49 years in sub-Saharan African countries using a Demographic and Health Surveys 2016–2023: a machine learning algorithm
Enthalten in BMC public health Bd. 25, 24.1.2025, Nr. 1, date:12.2025: 1-25
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10912 |
Predicting hospital-acquired pneumonia among schizophrenic patients: a machine learning approach
Enthalten in BMC medical informatics and decision making Bd. 19, 13.3.2019, Nr. 1, date:12.2019: 1-8
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10913 |
Predicting hospital length of stay using machine learning on a large open health dataset
Enthalten in BMC health services research Bd. 24, 29.7.2024, Nr. 1, date:12.2024: 1-29
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10914 |
Predicting hospital outpatient volume using XGBoost: a machine learning approach
Enthalten in Scientific reports Bd. 15, 16.5.2025, Nr. 1, date:12.2025: 1-13
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10915 |
Predicting hospitalization costs for pulmonary tuberculosis patients based on machine learning
Enthalten in BMC infectious diseases Bd. 24, 28.8.2024, Nr. 1, date:12.2024: 1-14
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10916 |
Predicting hospitalization following psychiatric crisis care using machine learning
Enthalten in BMC medical informatics and decision making Bd. 20, 10.12.2020, Nr. 1, date:12.2020: 1-11
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10917 |
Predicting host health status through an integrated machine learning framework: insights from healthy gut microbiome aging trajectory
Enthalten in Scientific reports Bd. 14, 28.12.2024, Nr. 1, date:12.2024: 1-11
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10918 |
Predicting humoral responses to primary and booster SARS-CoV-2 mRNA vaccination in people living with HIV: a machine learning approach
Enthalten in Journal of translational medicine Bd. 22, 7.5.2024, Nr. 1, date:12.2024: 1-9
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10919 |
Predicting Hurricane Evacuation Decisions with Interpretable Machine Learning Methods
Enthalten in International journal of disaster risk science Bd. 15, 5.3.2024, Nr. 1, date:2.2024: 134-148
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10920 |
Predicting in-hospital mortality after transcatheter aortic valve replacement using administrative data and machine learning
Enthalten in Scientific reports Bd. 13, 24.6.2023, Nr. 1, date:12.2023: 1-10
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Administration
