Deep Spatio-Temporal Representation and Ensemble Classification for Attention Deficit/Hyperactivity Disorder

Attention deficit/Hyperactivity disorder (ADHD) is a complex, universal and heterogeneous neurodevelopmental disease. The traditional diagnosis of ADHD relies on the long-term analysis of complex information such as clinical data (electroencephalogram, etc.), patients' behavior and psychologica...

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Veröffentlicht in:	IEEE transactions on neural systems and rehabilitation engineering Jg. 29; S. 1 - 10
Hauptverfasser:	Liu, Shuaiqi, Zhao, Ling, Wang, Xu, Xin, Qi, Zhao, Jie, Guttery, David S., Zhang, Yu-Dong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptive boosting decision tree ADHD Algorithms Artificial neural networks Attention deficit hyperactivity disorder Brain mapping Classification Classification algorithms Cognition Convolution convolutional denoising autoencoder Data mining Decision trees EEG Feature extraction fMRI classification Functional magnetic resonance imaging Machine learning Magnetic resonance imaging Neural networks Neurodevelopmental disorders Neuroimaging Noise reduction Physicians Psychological assessment Psychological tests Radiation Spatial data
ISSN:	1534-4320, 1558-0210, 1558-0210
Online-Zugang:	Volltext
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