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15641 |
Seasonality of acute kidney injury phenotypes in England: an unsupervised machine learning classification study of electronic health records
Enthalten in BMC nephrology Bd. 24, 9.8.2023, Nr. 1, date:12.2023: 1-9
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15642 |
Seasonally adjusted laboratory reference intervals to improve the performance of machine learning models for classification of cardiovascular diseases
Enthalten in BMC medical informatics and decision making Bd. 24, 4.3.2024, Nr. 1, date:12.2024: 1-11
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15643 |
SEAWEED PRESENCE DETECTION USING MACHINE LEARNING AND REMOTE SENSING
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLIII-B3-2022, 2022: 1011-1017. 7 S.
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15644 |
Second opinion machine learning for fast-track pathway assignment in hip and knee replacement surgery: the use of patient-reported outcome measures
Enthalten in BMC medical informatics and decision making Bd. 24, 23.7.2024, Nr. 4, date:12.2024: 1-17
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15645 |
Second opinion needed: communicating uncertainty in medical machine learning
Enthalten in npj digital medicine Bd. 4, 5.1.2021, Nr. 1, date:12.2021: 1-6
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15646 |
Second order Kalman filtering channel estimation and machine learning methods for spectrum sensing in cognitive radio networks
Enthalten in Wireless networks Bd. 27, 10.5.2021, Nr. 5, date:7.2021: 3273-3286
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15647 |
Secure machine learning against adversarial samples at test time
Enthalten in EURASIP journal on information security Bd. 2022, 12.1.2022, Nr. 1, date:12.2022: 1-15
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15648 |
Secure routing in the Internet of Things (IoT) with intrusion detection capability based on software-defined networking (SDN) and Machine Learning techniques
Enthalten in Scientific reports Bd. 13, 21.10.2023, Nr. 1, date:12.2023: 1-18
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15649 |
Securing 6G-enabled IoT/IoV networks by machine learning and data fusion
Enthalten in European Association for Speech, Signal and Image Processing: EURASIP journal on wireless communications and networking Bd. 2022, 22.11.2022, Nr. 1, date:12.2022: 1-17
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15650 |
Securing China’s rice harvest: unveiling dominant factors in production using multi-source data and hybrid machine learning models
Enthalten in Scientific reports Bd. 14, 26.6.2024, Nr. 1, date:12.2024: 1-16
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Administration
