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Die Lesesäle für Geisteswissenschaften, Naturwissenschaften, der Alte Lesesaal Technik und der Anne-Frank-Shoah-Lesesaal in Leipzig schließen am 04.02.2026 wegen einer Veranstaltung bereits um 15 Uhr. Die weiteren Lesesäle sowie die Servicetheke sind zu den regulären Zeiten geöffnet. //
The humanities reading room, the natural science reading room, the old technology reading room and the reading room of the Anne-Frank-Shoah-Library will close at 15:00 on 4 February 2026 due to an event. The other reading rooms and the service desk will be open during regular hours.

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33881 - 33890 von 34107

	33881	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
	33882	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
	33883	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
	33884	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
	33885	Validation of syncope short-term outcomes prediction by machine learning models in an Italian emergency department cohort Enthalten in Internal and emergency medicine Bd. 20, 16.7.2025, Nr. 5, date:8.2025: 1597-1605
	33886	Validation of the Toronto recurrence inference using machine-learning for post-transplant hepatocellular carcinoma model Enthalten in Communications medicine Bd. 5, 9.7.2025, Nr. 1, date:12.2025: 1-9
	33887	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
	33888	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
	33889	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
	33890	Value of machine learning in predicting TAVI outcomes Enthalten in Netherlands heart journal Bd. 27, 20.5.2019, Nr. 9, date:9.2019: 443-450

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