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Machine Learning Classification of Neuropsychiatric Systemi..:

, In: 2019 IEEE International Conference on Imaging Systems and Techniques (IST),

Simos, N. J. ; Manikis, G. C. ; Papadaki, E.... - p. 1-6 , 2019

Link: https://doi.org/10.1109/IST48021.2019.9010078

RT 
T1 <cTitle>2019 IEEE International Conference on Imaging Systems and Techniques (IST)</cTitle>: T1 <Title>Machine Learning Classification of Neuropsychiatric Systemic Lupus Erythematosus patients using resting-state fMRI functional connectivity</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-9010078&Exemplar=1&LAN=DE
				
A1 Simos, N. J.
A1 Manikis, G. C.
A1 Papadaki, E.
A1 Kavroulakis, E.
A1 Bertsias, G.
A1 Marias, K.
YR 2019
K1 Feature extraction
K1 Functional magnetic resonance imaging
K1 Support vector machines
K1 Measurement
K1 Time series analysis
K1 Machine learning
K1 Diseases
K1 Neuropsychiatric Systemic Lupus Erythematosus - NPSLE
K1 resting-state fMRI
K1 functional connectivity
K1 resting-state networks
K1 Machine Learning
K1 Supervised Learning
K1 Feature Selection
K1 Support Vector Machines
K1 Recursive Feature Elimination
K1 Nested Cross Validation
SP 1
OP 6
LK http://dx.doi.org/https://doi.org/10.1109/IST48021.2019.9010078
DO https://doi.org/10.1109/IST48021.2019.9010078
SF ELIB - SuUB Bremen

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