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34441 |
Validating administrative data to identify complex surgical site infections following cardiac implantable electronic device implantation: a comparison of traditional methods and machine learning
Enthalten in Antimicrobial resistance and infection control Bd. 11, 10.11.2022, Nr. 1, date:12.2022: 1-9
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34442 |
Validation of a blood biomarker panel for machine learning-based radiation biodosimetry in juvenile and adult C57BL/6 mice
Enthalten in Scientific reports Bd. 14, 12.10.2024, Nr. 1, date:12.2024: 1-10
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34443 |
Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48 h in advance using a diverse dataset from 461 US hospitals
Enthalten in BMC medical informatics and decision making Bd. 20, 27.10.2020, Nr. 1, date:12.2020: 1-10
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34444 |
Validation of a Machine Learning Algorithm, EVendo, for Predicting Esophageal Varices in Hepatocellular Carcinoma
Enthalten in Digestive diseases and sciences Bd. 69, 19.6.2024, Nr. 8, date:8.2024: 3079-3084
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34445 |
Validation of a machine learning model for indirect screening of suicidal ideation in the general population
Enthalten in Scientific reports Bd. 15, 24.2.2025, Nr. 1, date:12.2025: 1-10
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34446 |
Validation of a Natural Language Machine Learning Model for Safety Literature Surveillance
Enthalten in Drug safety Bd. 47, 8.11.2023, Nr. 1, date:1.2024: 71-80
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34447 |
Validation of machine learning models for estimation of left ventricular ejection fraction on point-of-care ultrasound: insights on features that impact performance
Enthalten in Echo Research and Practice Bd. 11, 28.3.2024, Nr. 1, date:12.2024: 1-10
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34448 |
Validation of machine learning models to detect amyloid pathologies across institutions
Enthalten in Acta Neuropathologica Communications Bd. 8, 28.4.2020, Nr. 1, date:12.2020: 1-13
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34449 |
Validity of Machine Learning in Assessing Large Texts Through Sustainability Indicators
Enthalten in Social indicators research Bd. 166, 26.1.2023, Nr. 2, date:4.2023: 323-337
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34450 |
Value and limitations of machine learning in high-frequency nutrient data for gap-filling, forecasting, and transport process interpretation
Enthalten in Environmental monitoring and assessment Bd. 195, 27.6.2023, Nr. 7, date:7.2023: 1-18
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Administration
