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11871 |
Regression prediction of tobacco chemical components during curing based on color quantification and machine learning
Enthalten in Scientific reports Bd. 14, 7.11.2024, Nr. 1, date:12.2024: 1-16
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11872 |
Regulatory Considerations on the use of Machine Learning based tools in Clinical Trials
Enthalten in Health and Technology Bd. 12, 7.11.2022, Nr. 6, date:11.2022: 1085-1096
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11873 |
Reimagining heritage villages’ sustainability: machine learning-driven human settlement suitability in Hunan
Enthalten in Humanities and Social Sciences Communications Bd. 12, 13.5.2025, Nr. 1, date:12.2025: 1-19
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11874 |
Relating plasticity to dislocation properties by data analysis: scaling vs. machine learning approaches
Enthalten in Materials theory Bd. 7, 3.1.2023, Nr. 1, date:12.2023: 1-15
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11875 |
Relation of gait measures with mild unilateral knee pain during walking using machine learning
Enthalten in Scientific reports Bd. 12, 23.12.2022, Nr. 1, date:12.2022: 1-9
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11876 |
Relationship between atherogenic index of plasma and length of stay in critically ill patients with atherosclerotic cardiovascular disease: a retrospective cohort study and predictive modeling based on machine learning
Enthalten in Cardiovascular diabetology Bd. 24, 28.2.2025, Nr. 1, date:12.2025: 1-16
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11877 |
Relationships between minerals’ intake and blood homocysteine levels based on three machine learning methods: a large cross-sectional study
Enthalten in Nutrition & Diabetes Bd. 14, 1.6.2024, Nr. 1, date:12.2024: 1-10
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11878 |
Relationships between motor and cognitive functions and subsequent post-stroke mood disorders revealed by machine learning analysis
Enthalten in Scientific reports Bd. 10, 11.11.2020, Nr. 1, date:12.2020: 1-10
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11879 |
Relative performance evaluation of machine learning algorithms for land use classification using multispectral moderate resolution data
Enthalten in SN applied sciences Bd. 5, 1.10.2023, Nr. 10, date:10.2023: 1-18
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11880 |
Relaxometric learning: a pattern recognition method for T 2 relaxation curves based on machine learning supported by an analytical framework
Enthalten in BMC chemistry Bd. 15, 20.2.2021, Nr. 1, date:12.2021: 1-8
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