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1 Ergebnisse
1
An Effective Connectomics Approach for Diagnosing ADHD usin..:
, In:
2021 11th International Conference on Computer Engineering and Knowledge (ICCKE)
,
Hamedi, Nastaran
;
Khadem, Ali
;
Vardast, Sajjad
.. - p. 110-114 , 2021
Link:
https://doi.org/10.1109/ICCKE54056.2021.9721443
RT T1 <cTitle>2021 11th International Conference on Computer Engineering and Knowledge (ICCKE)</cTitle>: T1 <Title>An Effective Connectomics Approach for Diagnosing ADHD using Eyes-open Resting-state MEG</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9721443&Exemplar=1&LAN=DE A1 Hamedi, Nastaran A1 Khadem, Ali A1 Vardast, Sajjad A1 Delrobaei, Mehdi A1 Babajani-Feremi, Abbas YR 2021 SN 2643-279X K1 Neurological diseases K1 Knowledge engineering K1 Stacking K1 Redundancy K1 Magnetoencephalography K1 Feature extraction K1 Classification algorithms K1 Attention Deficit Hyperactivity Disorder (ADHD) K1 Resting-state Magnetoencephalography (rs-MEG) K1 Effective connectivity K1 Granger Causality (GC) K1 Machine learning K1 minimum redundancy maximum relevance (mRMR) feature selection SP 110 OP 114 LK http://dx.doi.org/https://doi.org/10.1109/ICCKE54056.2021.9721443 DO https://doi.org/10.1109/ICCKE54056.2021.9721443 SF ELIB - SuUB Bremen
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