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26021 |
Prediction of cytochrome P450-mediated bioactivation using machine learning models and in vitro validation
Enthalten in Archives of toxicology Bd. 98, 16.3.2024, Nr. 5, date:5.2024: 1457-1467
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26022 |
Prediction of daily sea water temperature in Turkish seas using machine learning approaches
Enthalten in Arabian journal of geosciences Bd. 15, 19.10.2022, Nr. 21, date:11.2022: 1-19
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26023 |
Prediction of damage potential in mainshock–aftershock sequences using machine learning algorithms
Enthalten in Earthquake engineering and engineering vibration Bd. 23, 8.10.2024, Nr. 4, date:10.2024: 919-938
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26024 |
PREDICTION OF DEFORMATION CAUSED BY LANDSLIDES BASED ON GRAPH CONVOLUTION NETWORKS ALGORITHM AND DINSAR TECHNIQUE
Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. X-4/W1-2022, 2023: 391-397. 7 S.
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26025 |
Prediction of delayed graft function after kidney transplantation: comparison between logistic regression and machine learning methods
Enthalten in BMC medical informatics and decision making Bd. 15, 14.10.2015, Nr. 1, date:12.2015: 1-10
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26026 |
Prediction of dengue outbreak in Selangor Malaysia using machine learning techniques
Enthalten in Scientific reports Bd. 11, 13.1.2021, Nr. 1, date:12.2021: 1-9
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26027 |
Prediction of depression risk in middle-aged and elderly Cardiovascular-Kidney-Metabolic syndrome patients by social and environmental determinants of health: an interpretable machine learning approach using longitudinal data from China
Enthalten in Journal of health, population and nutrition Bd. 44, 4.6.2025, Nr. 1, date:12.2025: 1-15
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26028 |
Prediction of depressive disorder using machine learning approaches: findings from the NHANES
Enthalten in BMC medical informatics and decision making Bd. 25, 17.2.2025, Nr. 1, date:12.2025: 1-12
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26029 |
Prediction of diabetes disease using an ensemble of machine learning multi-classifier models
Enthalten in BMC bioinformatics Bd. 24, 12.9.2023, Nr. 1, date:12.2023: 1-24
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26030 |
Prediction of disease progression and outcomes in multiple sclerosis with machine learning
Enthalten in Scientific reports Bd. 10, 3.12.2020, Nr. 1, date:12.2020: 1-13
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