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Ergebnis der Suche nach: "Machine Learning"
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16401 - 16410 von 16964

	16401	The predictive value of machine learning for mortality risk in patients with acute coronary syndromes: a systematic review and meta-analysis Enthalten in European journal of medical research Bd. 28, 20.10.2023, Nr. 1, date:12.2023: 1-13
	16402	The Promise of Artificial Intelligence and Machine Learning in Geriatric Anesthesiology Education: An Idea Whose Time Has Come Enthalten in Current anesthesiology reports Bd. 15, 6.1.2025, Nr. 1, date:12.2025: 1-10
	16403	The promise of machine learning applications in solid organ transplantation Enthalten in npj digital medicine Bd. 5, 11.7.2022, Nr. 1, date:12.2022: 1-13
	16404	The quest for a biological phenotype of adolescent non-suicidal self-injury: a machine-learning approach Enthalten in Translational Psychiatry Bd. 14, 25.1.2024, Nr. 1, date:12.2024: 1-7
	16405	The quest for the reliability of machine learning models in binary classification on tabular data Enthalten in Scientific reports Bd. 13, 27.10.2023, Nr. 1, date:12.2023: 1-11
	16406	The ReadFree tool for the identification of poor readers: a validation study based on a machine learning approach in monolingual and minority-language children Enthalten in Annals of dyslexia Bd. 73, 7.8.2023, Nr. 3, date:10.2023: 356-392
	16407	The regression analysis of dry - wet wear outcomes and materials properties of biodegradable MgCu and MgZn, made by P/M, using machine learning models Enthalten in Applied physics / A / Materials science & processing Bd. 131, 24.3.2025, Nr. 4, date:4.2025: 1-19
	16408	The relative data hungriness of unpenalized and penalized logistic regression and ensemble-based machine learning methods: the case of calibration Enthalten in Diagnostic and prognostic research Bd. 8, 5.11.2024, Nr. 1, date:12.2024: 1-18
	16409	The remarkable potential of machine learning algorithms in estimating water permeability of concrete incorporating nano natural pozzolana Enthalten in Scientific reports Bd. 14, 31.5.2024, Nr. 1, date:12.2024: 1-22
	16410	The risk factors determined by four machine learning methods for the change of difference of bone mineral density in post-menopausal women after three years follow-up Enthalten in Scientific reports Bd. 14, 5.10.2024, Nr. 1, date:12.2024: 1-14

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