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25671 |
Prediction and feature selection of low birth weight using machine learning algorithms
Enthalten in Journal of health, population and nutrition Bd. 43, 12.10.2024, Nr. 1, date:12.2024: 1-13
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25672 |
Prediction and in-depth analysis of precast concrete strength by machine learning
Enthalten in Innovative infrastructure solutions Bd. 10, 3.3.2025, Nr. 3, date:3.2025: 1-18
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25673 |
Prediction and optimization of hardness in AlSi10Mg alloy produced by laser powder bed fusion using statistical and machine learning approaches
Enthalten in Scientific reports Bd. 15, 23.5.2025, Nr. 1, date:12.2025: 1-9
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25674 |
Prediction and optimization of indirect shoot regeneration of Passiflora caerulea using machine learning and optimization algorithms
Enthalten in BMC biotechnology Bd. 23, 1.8.2023, Nr. 1, date:12.2023: 1-12
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25675 |
Prediction and optimization of stretch flangeability of advanced high strength steels utilizing machine learning approaches
Enthalten in Scientific reports Bd. 15, 10.5.2025, Nr. 1, date:12.2025: 1-21
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25676 |
Prediction and parametric assessment of soil one-dimensional vertical free swelling potential using ensemble machine learning models
Enthalten in Advanced modeling and simulation in engineering sciences Bd. 11, 27.12.2024, Nr. 1, date:12.2024: 1-20
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25677 |
Prediction and risk assessment of sepsis-associated encephalopathy in ICU based on interpretable machine learning
Enthalten in Scientific reports Bd. 12, 31.12.2022, Nr. 1, date:12.2022: 1-11
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25678 |
Prediction and unsupervised clustering of fertility intention among migrant workers based on machine learning: a cross-sectional survey from Henan, China
Enthalten in BMC public health Bd. 25, 14.1.2025, Nr. 1, date:12.2025: 1-9
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25679 |
Prediction and validation of fire parameters for a self-extinguishing and smoke suppressant electrospun PVP-based multilayer material through machine learning models
Enthalten in Journal of materials science Bd. 60, 28.12.2024, Nr. 2, date:1.2025: 1019-1040
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25680 |
Prediction and validation of mechanical properties of self-compacting geopolymer concrete using combined machine learning methods a comparative and suitability assessment of the best analysis
Enthalten in Scientific reports Bd. 15, 21.2.2025, Nr. 1, date:12.2025: 1-53
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