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Ergebnis der Suche nach:
tit all "Machine Learning Techniques"
im Bestand: Gesamter Bestand
1041 - 1050 von 1449
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1041
Hypoxia Detection for Confined-Space Workers: Photoplethysmography and Machine-Learning Techniques
Enthalten in SN Computer Science Bd. 3, 16.5.2022, Nr. 4, date:7.2022: 1-11
1042
Identification of bipolar disorder using a combination of multimodality magnetic resonance imaging and machine learning techniques
Enthalten in BMC psychiatry Bd. 20, 6.10.2020, Nr. 1, date:12.2020: 1-12
1043
Identification of infectious disease-associated host genes using machine learning techniques
Enthalten in BMC bioinformatics Bd. 20, 27.12.2019, Nr. 1, date:12.2019: 1-12
1044
Identification of tqg flavor-changing neutral current interactions using machine learning techniques
Enthalten in Han'guk-Mulli-Hakhoe: Journal of the Korean Physical Society Bd. 86, 6.1.2025, Nr. 4, date:2.2025: 269-279
1045
Identifying comparative opinions in Arabic text in social media using machine learning techniques
Enthalten in SN applied sciences Bd. 1, 4.2.2019, Nr. 3, date:3.2019: 1-13
1046
Identifying influential factors using machine learning techniques on the intention to receive a COVID-19 booster dose and vaccine fatigue among partially vaccinated individuals
Enthalten in Discover public health Bd. 21, 7.11.2024, Nr. 1, date:12.2024: 1-17
1047
Identifying the candidate genes using co-expression, GO, and machine learning techniques for Alzheimer’s disease
Enthalten in Network modeling analysis in health informatics and bioinformatics Bd. 11, 4.2.2022, Nr. 1, date:12.2022: 1-12
1048
Identifying the most important workplace factors in predicting nurse mental health using machine learning techniques
Enthalten in BMC nursing Bd. 20, 1.11.2021, Nr. 1, date:12.2021: 1-10
1049
Identifying the presence and severity of dementia by applying interpretable machine learning techniques on structured clinical records
Enthalten in BMC medical informatics and decision making Bd. 22, 17.10.2022, Nr. 1, date:12.2022: 1-20
1050
Imaging neutron capture cross sections: i-TED proof-of-concept and future prospects based on Machine-Learning techniques
Enthalten in The European physical journal / A / Hadrons and nuclei Bd. 57, 17.6.2021, Nr. 6, date:6.2021: 1-17
1041 - 1050 von 1449
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