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25981 |
Prediction of blood pressure variability during thrombectomy using supervised machine learning and outcomes of patients with ischemic stroke from large vessel occlusion
Enthalten in Journal of thrombosis and thrombolysis Bd. 56, 12.4.2023, Nr. 1, date:7.2023: 12-26
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25982 |
Prediction of bloodstream infection using machine learning based primarily on biochemical data
Enthalten in Scientific reports Bd. 15, 20.5.2025, Nr. 1, date:12.2025: 1-13
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25983 |
Prediction of Boiling Crisis in Channels Using Machine Learning Algorithms
Enthalten in Optoelectronics, instrumentation and data processing Bd. 58, 8.7.2022, Nr. 1, date:2.2022: 98-108
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25984 |
Prediction of buckling damage of steel equal angle structural members using hybrid machine learning techniques
Enthalten in Scientific reports Bd. 15, 8.2.2025, Nr. 1, date:12.2025: 1-11
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25985 |
Prediction of cadmium content using machine learning methods
Enthalten in Environmental earth sciences Bd. 83, 27.5.2024, Nr. 12, date:6.2024: 1-11
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25986 |
Prediction of carbapenem-resistant gram-negative bacterial bloodstream infection in intensive care unit based on machine learning
Enthalten in BMC medical informatics and decision making Bd. 24, 14.5.2024, Nr. 1, date:12.2024: 1-11
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25987 |
Prediction of Carbonation Depth for Concrete Containing Mineral Admixtures Based on Machine Learning
Enthalten in The Arabian journal for science and engineering Bd. 48, 9.3.2023, Nr. 10, date:10.2023: 13211-13225
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25988 |
Prediction of cardiac arrest in critically ill patients presenting to the emergency department using a machine learning score incorporating heart rate variability compared with the modified early warning score
Enthalten in Critical care Bd. 16, 21.6.2012, Nr. 3, date:6.2012: 1-12
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25989 |
Prediction of CBR and resilient modulus of crushed waste rocks using machine learning models
Enthalten in Acta geotechnica Bd. 17, 2.4.2022, Nr. 4, date:4.2022: 1383-1402
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25990 |
Prediction of cell migration potential on human breast cancer cells treated with Albizia lebbeck ethanolic extract using extreme machine learning
Enthalten in Scientific reports Bd. 13, 14.12.2023, Nr. 1, date:12.2023: 1-16
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Administration
