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27691 |
Using machine learning techniques to predict the risk of osteoporosis based on nationwide chronic disease data
Enthalten in Scientific reports Bd. 14, 4.3.2024, Nr. 1, date:12.2024: 1-11
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27692 |
Using Machine Learning Techniques to Test the Load Capacity Curve Hypothesis: A Classifier-Lasso Application on Global Panel Data
Enthalten in Biophysical economics and sustainability Bd. 10, 19.2.2025, Nr. 1, date:6.2025: 1-18
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27693 |
Using machine learning to assist with the selection of security controls during security assessment
Enthalten in Empirical software engineering Bd. 25, 13.4.2020, Nr. 4, date:7.2020: 2550-2582
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27694 |
Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials
Enthalten in Theoretical and applied genetics Bd. 137, 23.7.2024, Nr. 8, date:8.2024: 1-13
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27695 |
Using machine learning to detect network intrusions in industrial control systems: a survey
Enthalten in International journal of information security Bd. 24, 8.11.2024, Nr. 1, date:2.2025: 1-16
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27696 |
Using machine learning to detect the differential usage of novel gene isoforms
Enthalten in BMC bioinformatics Bd. 23, 18.1.2022, Nr. 1, date:12.2022: 1-16
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27697 |
Using machine learning to determine age over 16 based on development of third molar and periodontal ligament of second molar
Enthalten in BMC oral health Bd. 23, 20.9.2023, Nr. 1, date:12.2023: 1-9
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27698 |
Using machine learning to determine the correlation between physiological and environmental parameters and the induction of acute mountain sickness
Enthalten in BMC bioinformatics Bd. 22, 31.5.2022, Nr. 5, date:11.2021: 1-14
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27699 |
Using machine learning to determine the time of exposure to infection by a respiratory pathogen
Enthalten in Scientific reports Bd. 13, 1.4.2023, Nr. 1, date:12.2023: 1-10
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27700 |
Using machine learning to develop a clinical prediction model for SSRI-associated bleeding: a feasibility study
Enthalten in BMC medical informatics and decision making Bd. 23, 11.6.2023, Nr. 1, date:12.2023: 1-11
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