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26411 - 26420 von 27932

	26411	Smartphones, Sensors, and Machine Learning to Advance Real-Time Prediction and Interventions for Suicide Prevention: a Review of Current Progress and Next Steps Enthalten in Current psychiatry reports Bd. 20, 28.6.2018, Nr. 7, date:7.2018: 1-6
	26412	Smoke testing for machine learning: simple tests to discover severe bugs Enthalten in Empirical software engineering Bd. 27, 21.1.2022, Nr. 2, date:3.2022: 1-30
	26413	Smooth input preparation for quantum and quantum-inspired machine learning Enthalten in Quantum machine intelligence Bd. 3, 26.4.2021, Nr. 1, date:6.2021: 1-6
	26414	SMOTE and ExtraTreesRegressor based random forest technique for predicting Australian rainfall Enthalten in International journal of information technology Bd. 15, 1.3.2023, Nr. 3, date:3.2023: 1679-1687
	26415	SMR-guided molecular subtyping and machine learning model reveals novel prognostic biomarkers and therapeutic targets in non-small cell lung adenocarcinoma Enthalten in Scientific reports Bd. 15, 10.1.2025, Nr. 1, date:12.2025: 1-18
	26416	SNooPer: a machine learning-based method for somatic variant identification from low-pass next-generation sequencing Enthalten in BMC genomics Bd. 17, 14.11.2016, Nr. 1, date:12.2016: 1-11
	26417	Snow and glacial feature identification using Hyperion dataset and machine learning algorithms Enthalten in Arabian journal of geosciences Bd. 14, 28.7.2021, Nr. 15, date:8.2021: 1-21
	26418	SNOW AVALANCHE SUSCEPTIBILITY MAPPING FOR DAVOS, SWITZERLAND Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLIII-B3-2022, 2022: 1083-1090. 8 S.
	26419	Snow avalanche susceptibility mapping using novel tree-based machine learning algorithms (XGBoost, NGBoost, and LightGBM) with eXplainable Artificial Intelligence (XAI) approach Enthalten in Stochastic environmental research and risk assessment Bd. 37, 13.3.2023, Nr. 6, date:6.2023: 2243-2270
	26420	Snow cover estimation from MODIS and Sentinel-1 SAR data using machine learning algorithms in the western part of the Tianshan Mountains Enthalten in Journal of mountain science Bd. 17, 11.4.2020, Nr. 4, date:4.2020: 884-897

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