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	1451	Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions Enthalten in International journal of computer assisted radiology and surgery Bd. 11, 8.10.2015, Nr. 4, date:4.2016: 553-568
	1452	Survey of machine learning techniques for Arabic fake news detection Enthalten in Artificial intelligence review Bd. 57, 28.5.2024, Nr. 6, date:6.2024: 1-33
	1453	Survey on Machine Learning and Deep Learning Techniques for Agriculture Land Enthalten in SN Computer Science Bd. 2, 18.10.2021, Nr. 6, date:11.2021: 1-12
	1454	Survival prediction models since liver transplantation - comparisons between Cox models and machine learning techniques Enthalten in BMC medical research methodology Bd. 20, 16.11.2020, Nr. 1, date:12.2020: 1-14
	1455	Survival prediction of glioblastoma patients using modern deep learning and machine learning techniques Enthalten in Scientific reports Bd. 14, 29.1.2024, Nr. 1, date:12.2024: 1-12
	1456	Swarm optimization based heterogeneous machine learning techniques for enhanced landslide susceptibility assessment with comprehensive uncertainty quantification Enthalten in Earth science informatics Bd. 18, 4.1.2025, Nr. 1, date:1.2025: 1-34
	1457	Symptom clusters among cancer survivors: what can machine learning techniques tell us? Enthalten in BMC medical research methodology Bd. 21, 16.8.2021, Nr. 1, date:12.2021: 1-12
	1458	Synergetic use of geospatial and machine learning techniques in modelling landslide susceptibility in parts of Shimla to Kinnaur National Highway, Himachal Pradesh Enthalten in Modeling earth systems and environment Bd. 10, 18.4.2024, Nr. 3, date:6.2024: 4163-4183
	1459	Synergistic integration of Multi-View Brain Networks and advanced machine learning techniques for auditory disorders diagnostics Enthalten in Brain Informatics Bd. 11, 14.1.2024, Nr. 1, date:12.2024: 1-13
	1460	Synergizing multiple machine learning techniques and remote sensing for advanced landslide susceptibility assessment: a case study in the Three Gorges Reservoir Area Enthalten in Environmental earth sciences Bd. 83, 2.4.2024, Nr. 8, date:4.2024: 1-20

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