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15991 |
Stability modeling for chatter avoidance in self-aware machining: an application of physics-guided machine learning
Enthalten in Journal of intelligent manufacturing Bd. 34, 9.11.2022, Nr. 1, date:1.2023: 387-413
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15992 |
Stabilization of nonlinear safety-critical systems by relaxed converse Lyapunov-barrier approach and its applications in robotic systems
Enthalten in Autonomous intelligent systems Bd. 4, 19.11.2024, Nr. 1, date:12.2024: 1-8
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15993 |
Stable patients with suspected myocardial ischemia: comparison of machine-learning computed tomography-based fractional flow reserve and stress perfusion cardiovascular magnetic resonance imaging to detect myocardial ischemia
Enthalten in BMC cardiovascular disorders Bd. 22, 5.2.2022, Nr. 1, date:12.2022: 1-10
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15994 |
Stacked ensemble machine learning for porosity and absolute permeability prediction of carbonate rock plugs
Enthalten in Scientific reports Bd. 13, 17.6.2023, Nr. 1, date:12.2023: 1-17
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15995 |
Stacked machine learning models for accurate estimation of shear and Stoneley wave transit times in DSI log
Enthalten in Scientific reports Bd. 15, 14.3.2025, Nr. 1, date:12.2025: 1-22
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15996 |
Stacked machine learning models for predicting species richness and endemism for Mediterranean endemic plants in the Mareotis subsector in Egypt
Enthalten in Plant ecology Bd. 224, 14.11.2023, Nr. 12, date:12.2023: 1113-1126
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15997 |
Stacking classifiers based on integrated machine learning model: fusion of CT radiomics and clinical biomarkers to predict lymph node metastasis in locally advanced gastric cancer patients after neoadjuvant chemotherapy
Enthalten in BMC cancer Bd. 25, 6.5.2025, Nr. 1, date:12.2025: 1-12
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15998 |
Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes
Enthalten in European journal of nuclear medicine and molecular imaging Bd. 47, 28.12.2019, Nr. 8, date:7.2020: 1971-1983
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15999 |
Staging of colorectal cancer using lipid biomarkers and machine learning
Enthalten in Metabolomics Bd. 19, 20.9.2023, Nr. 10, date:10.2023: 1-11
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16000 |
State-of-the-art for automated machine learning predicts outcomes in poor-grade aneurysmal subarachnoid hemorrhage using routinely measured laboratory & radiological parameters: coagulation parameters and liver function as key prognosticators
Enthalten in Neurosurgical review Bd. 48, 17.3.2025, Nr. 1, date:12.2025: 1-11
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