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40101 |
Using machine learning to estimate the incidence rate of intimate partner violence
Enthalten in Scientific reports Bd. 13, 4.4.2023, Nr. 1, date:12.2023: 1-9
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40102 |
Using machine learning to examine the relationship between asthma and absenteeism
Enthalten in Environmental monitoring and assessment Bd. 191, 28.6.2019, Nr. 2, date:6.2019: 1-9
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40103 |
Using machine learning to explore core risk factors associated with the risk of eating disorders among non-clinical young women in China: A decision-tree classification analysis
Enthalten in Journal of eating disorders Bd. 10, 10.2.2022, Nr. 1, date:12.2022: 1-11
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40104 |
Using machine learning to explore the determinants of service satisfaction with online healthcare platforms during the COVID-19 pandemic
Enthalten in Service business Bd. 17, 16.5.2023, Nr. 2, date:6.2023: 449-476
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40105 |
Using machine learning to explore the efficacy of administrative variables in prediction of subjective-wellbeing outcomes in New Zealand
Enthalten in Scientific reports Bd. 15, 25.2.2025, Nr. 1, date:12.2025: 1-10
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40106 |
Using machine learning to find the hidden relationship between RTT and TCP throughput in WiFi
Enthalten in European Association for Speech, Signal and Image Processing: EURASIP journal on wireless communications and networking Bd. 2021, 20.12.2021, Nr. 1, date:12.2021: 1-18
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40107 |
Using machine learning to forecast conflict events for use in forced migration models
Enthalten in Scientific reports Bd. 15, 2.8.2025, Nr. 1, date:12.2025: 1-14
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40108 |
Using machine learning to forecast domestic homicide via police data and super learning
Enthalten in Scientific reports Bd. 13, 21.12.2023, Nr. 1, date:12.2023: 1-8
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40109 |
Using Machine Learning to Forecast Future Earnings
Enthalten in Atlantic economic journal Bd. 48, 21.1.2021, Nr. 4, date:12.2020: 543-545
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40110 |
Using Machine Learning to Identify and Optimize Sensitive Parameters in Urban Flood Model Considering Subsurface Characteristics
Enthalten in International journal of disaster risk science Bd. 15, 21.2.2024, Nr. 1, date:2.2024: 116-133
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Administration
