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15511 |
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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15512 |
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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15513 |
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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15514 |
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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15515 |
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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15516 |
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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15517 |
Using machine learning to identify gene interaction networks associated with breast cancer
Enthalten in BMC cancer Bd. 22, 17.10.2022, Nr. 1, date:12.2022: 1-9
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15518 |
Using machine learning to improve the accuracy of genomic prediction of reproduction traits in pigs
Enthalten in Journal of animal science and biotechnology Bd. 13, 17.5.2022, Nr. 1, date:12.2022: 1-12
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15519 |
Using Machine Learning to Measure Relatedness Between Genes: A Multi-Features Model
Enthalten in Scientific reports Bd. 9, 12.3.2019, Nr. 1, date:12.2019: 1-15
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15520 |
Using machine learning to mine mental health diagnostic groups from emergency department presentations before and during the COVID-19 pandemic
Enthalten in Discover mental health Bd. 3, 6.11.2023, Nr. 1, date:12.2023: 1-22
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Administration
