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42861 |
Using machine learning-based radiomics to differentiate between glioma and solitary brain metastasis from lung cancer and its subtypes
Enthalten in Discover oncology Bd. 14, 6.12.2023, Nr. 1, date:12.2023: 1-10
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42862 |
USING MACHINE LEARNING CLASSIFIERS AND REGRESSION MODELS FOR ESTIMATING THE STAND AGES OF FALCATA PLANTATIONS FROM SENTINEL DATA
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-4/W6-2022, 2023: 465-472. 8 S.
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42863 |
USING MACHINE LEARNING COUPLED WITH REMOTE SENSING FOR FOREST FIRE SUSCEPTIBILITY MAPPING. CASE STUDY TETOUAN PROVINCE, NORTHERN MOROCCO
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-4/W6-2022, 2023: 333-342. 10 S.
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42864 |
Using machine learning for communication classification
Enthalten in Experimental economics Bd. 22, 14.2.2019, Nr. 4, date:12.2019: 1002-1029
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42865 |
Using machine learning for early detection of chronic obstructive pulmonary disease: a narrative review
Enthalten in Respiratory research Bd. 25, 9.9.2024, Nr. 1, date:12.2024: 1-9
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42866 |
Using machine learning for early prediction of in-hospital mortality during ICU admission in liver cancer patients
Enthalten in Scientific reports Bd. 15, 18.11.2025, Nr. 1, date:12.2025: 1-10
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42867 |
Using machine learning for model benchmarking and forecasting of depletion-induced seismicity in the Groningen gas field
Enthalten in Computational geosciences Bd. 25, 3.1.2021, Nr. 1, date:2.2021: 529-551
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42868 |
Using machine learning for predicting cancer-specific mortality in bladder cancer patients undergoing radical cystectomy: a SEER-based study
Enthalten in BMC cancer Bd. 25, 21.3.2025, Nr. 1, date:12.2025: 1-13
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42869 |
Using Machine Learning for Robust Target Prediction in a Basic Oxygen Furnace System
Enthalten in Metallurgical and materials transactions / B / Process metallurgy and materials processing science Bd. 51, 29.5.2020, Nr. 4, date:8.2020: 1632-1645
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42870 |
Using machine learning for the assessment of ecological status of unmonitored waters in Poland
Enthalten in Scientific reports Bd. 14, 18.10.2024, Nr. 1, date:12.2024: 1-14
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