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Ergebnis der Suche nach: "Machine Learning"
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	16951	Validating The Philippine Mangrove Map 2023 through Capacity Building and Crowdsourcing Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. X-5-2024, 2024: 243-250. 8 S.
	16952	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
	16953	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
	16954	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
	16955	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
	16956	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
	16957	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
	16958	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
	16959	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
	16960	Value of Geologically Derived Features in Machine Learning Facies Classification Enthalten in Mathematical geosciences Bd. 52, 16.11.2019, Nr. 1, date:1.2020: 5-29

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