Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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	501	Advancements and future trends in machine learning for lung cancer: a comprehensive bibliometric analysis Enthalten in Clinical and translational oncology 4.6.2025: 1-12
	502	An approach based on machine learning and mel-frequency cepstral coefficients for locating faults in transmission lines Enthalten in Energy systems 4.6.2025: 1-28
	503	Anoikis-Related Genes Can Accurately Predict the Occurrence of Endometriosis: A Retrospective Cohort Study via Machine Learning Analysis Enthalten in Biochemical genetics 4.6.2025: 1-20
	504	Answer to the Letter to the Editor of H. Daungsupawong, et al. concerning “A multimodal machine learning model integrating clinical and MRI data for predicting neurological outcomes following surgical treatment for cervical spinal cord injury” by Shimizu T, et al. (Eur Spine J [2025]: doi: 10.1007/s00586-025-08873-2) Enthalten in European spine journal 4.6.2025: 1
	505	Answer to the Letter to the Editor of W. Yue, et al. concerning “A multimodal machine learning model integrating clinical and MRI data for predicting neurological outcomes following surgical treatment for cervical spinal cord injury” by Shimizu T, et al. (Eur Spine J [2025]: doi: 10.1007/s00586-025-08873-2) Enthalten in European spine journal 4.6.2025: 1-2
	506	CLRD-GLPS: A Long-term Seasonal Dataset of Ruminant Livestock Distribution in China's Grazing Production Systems (2000–2021) Using Stacking-based Interpretable Machine Learning Enthalten in Earth system science data discussions 04.06.2025: 1-45. 45 S.
	507	Investigating the association between groundwater contaminants and hypertension risk in India: a machine learning-based analysis Enthalten in Journal of exposure science & environmental epidemiology 4.6.2025: 1-18
	508	Letter to the Editor concerning “A multimodal machine learning model integrating clinical and MRI data for predicting neurological outcomes following surgical treatment for cervical spinal cord injury” by Shimizu T, et al. (Eur Spine J [2025]: doi: 10.1007/s00586-025-08873-2) Enthalten in European spine journal 4.6.2025: 1-2
	509	Machine learning-driven power demand forecasting models for optimized power management Enthalten in Electrical engineering 4.6.2025: 1-26
	510	Machine Learning-Enhanced Surface Plasmon Resonance Sensor with D-Shaped Dual-Core Photonic Crystal Fiber Design Enthalten in Journal of fluorescence 4.6.2025: 1-14

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