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Ergebnis der Suche nach: "Machine Learning"
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17001 - 17010 von 17108

	17001	Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine) Enthalten in Scientific reports Bd. 15, 24.1.2025, Nr. 1, date:12.2025: 1-13
	17002	Utilizing machine learning to predict participant response to follow-up health surveys in the Millennium Cohort Study Enthalten in Scientific reports Bd. 14, 28.10.2024, Nr. 1, date:12.2024: 1-12
	17003	Utilizing machine learning to predict post-treatment outcomes in chronic non-specific neck pain patients undergoing cervical extension traction Enthalten in Scientific reports Bd. 14, 23.5.2024, Nr. 1, date:12.2024: 1-13
	17004	Utilizing Ni(II) complex for metal drug-gel particles in cervical cancer treatment and designing novel drugs through machine learning methods Enthalten in Scientific reports Bd. 14, 5.3.2024, Nr. 1, date:12.2024: 1-9
	17005	Utilizing reinforcement learning for de novo drug design Enthalten in Machine learning Bd. 113, 8.4.2024, Nr. 7, date:7.2024: 4811-4843
	17006	Utilizing SMOTE-TomekLink and machine learning to construct a predictive model for elderly medical and daily care services demand Enthalten in Scientific reports Bd. 15, 11.3.2025, Nr. 1, date:12.2025: 1-12
	17007	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
	17008	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.
	17009	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
	17010	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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