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11891 |
Using Machine Learning Hardware to Solve Linear Partial Differential Equations with Finite Difference Methods
Enthalten in International journal of parallel programming Bd. 53, 4.3.2025, Nr. 2, date:4.2025: 1-22
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11892 |
Using machine learning in pediatric cardio-oncology: we have the questions, we need the answers
Enthalten in Cardio-Oncology Bd. 10, 6.11.2024, Nr. 1, date:12.2024: 1-3
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11893 |
Using machine learning methods to predict 28-day mortality in patients with hepatic encephalopathy
Enthalten in BMC gastroenterology Bd. 23, 6.4.2023, Nr. 1, date:12.2023: 1-11
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11894 |
Using machine learning methods to predict electric vehicles penetration in the automotive market
Enthalten in Scientific reports Bd. 13, 23.5.2023, Nr. 1, date:12.2023: 1-16
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11895 |
Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU
Enthalten in BMC medical informatics and decision making Bd. 20, 2.10.2020, Nr. 1, date:12.2020: 1-10
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11896 |
Using machine learning model explanations to identify proteins related to severity of meibomian gland dysfunction
Enthalten in Scientific reports Bd. 13, 22.12.2023, Nr. 1, date:12.2023: 1-13
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|
|
11897 |
Using machine learning models to improve stroke risk level classification methods of China national stroke screening
Enthalten in BMC medical informatics and decision making Bd. 19, 10.12.2019, Nr. 1, date:12.2019: 1-7
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11898 |
Using machine-learning models to predict extubation failure in neonates with bronchopulmonary dysplasia
Enthalten in BMC pulmonary medicine Bd. 24, 1.7.2024, Nr. 1, date:12.2024: 1-9
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11899 |
Using machine learning of clinical data to diagnose COVID-19: a systematic review and meta-analysis
Enthalten in BMC medical informatics and decision making Bd. 20, 29.9.2020, Nr. 1, date:12.2020: 1-13
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|
11900 |
Using machine learning on clinical data to identify unexpected patterns in groups of COVID-19 patients
Enthalten in Scientific reports Bd. 13, 8.2.2023, Nr. 1, date:12.2023: 1-11
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Administration
