Machine learning in preoperative glioma MRI: survival associations by perfusion-based support vector machine outperforms traditional MRI.
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[Quantitative perfusion imaging in magnetic resonance imaging].Diffusion Kurtosis Imaging of Gliomas Grades II and III - A Study of Perilesional Tumor Infiltration, Tumor Grades and Subtypes at Clinical Presentation.Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.Oxygen extraction fraction mapping at 3 Tesla using an artificial neural network: A feasibility study.An imaging-based approach predicts clinical outcomes in prostate cancer through a novel support vector machine classification.Diffusion parameter mapping with the combined intravoxel incoherent motion and kurtosis model using artificial neural networks at 3 T.MRI features predict p53 status in lower-grade gliomas via a machine-learning approach.
P2860
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P2860
Machine learning in preoperative glioma MRI: survival associations by perfusion-based support vector machine outperforms traditional MRI.
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Machine learning in preoperati ...... e outperforms traditional MRI.
@en
Machine learning in preoperati ...... e outperforms traditional MRI.
@nl
type
label
Machine learning in preoperati ...... e outperforms traditional MRI.
@en
Machine learning in preoperati ...... e outperforms traditional MRI.
@nl
prefLabel
Machine learning in preoperati ...... e outperforms traditional MRI.
@en
Machine learning in preoperati ...... e outperforms traditional MRI.
@nl
P2093
P2860
P50
P356
P1476
Machine learning in preoperati ...... ne outperforms traditional MRI
@en
P2093
Atle Bjornerud
David Scheie
Frank G Zoellner
John K Hald
Lothar R Schad
P2860
P356
10.1002/JMRI.24390
P577
2013-11-13T00:00:00Z