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17721 |
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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17722 |
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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17723 |
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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17724 |
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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17725 |
Using machine learning to develop a five-item short form of the children’s depression inventory
Enthalten in BMC public health Bd. 24, 23.4.2024, Nr. 1, date:12.2024: 1-11
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17726 |
Using machine learning to develop a stacking ensemble learning model for the CT radiomics classification of brain metastases
Enthalten in Scientific reports Bd. 14, 19.11.2024, Nr. 1, date:12.2024: 1-11
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17727 |
Using machine learning to discover DNA metabolism biomarkers that direct prostate cancer treatment
Enthalten in Scientific reports Bd. 15, 18.7.2025, Nr. 1, date:12.2025: 1-18
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17728 |
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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17729 |
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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17730 |
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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Administration
