Concepedia

Author

Amirali Vahid

Technische Universität DresdenORCID

Also Known As

Amirali Vahid

20

Publications

505

Citations

9

H-Index

22

Concepts

All Affiliations

Technische Universität DresdenOtto-von-Guericke University MagdeburgUniversity Hospital Carl Gustav CarusCharité - Universitätsmedizin Berlin
AV

About

Amirali Vahid is an author at Technische Universität Dresden specializing in cognitive science, cognitive neuroscience, and social sciences.

Top Concepts

#ConceptH-IndexPublicationsCitations

1

Social Sciences

2

2

121

2

Cognitive Science

2

2

121

3

Engineering

1

1

12

4

Medicine

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1

109

5

Neurology

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109

Amirali Vahid

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8

Publications

478

Citations

8

H-Index

YearCitations

Machine learning provides novel neurophysiological features that predict performance to inhibit automated responses

Amirali Vahid, Moritz Mückschel, Andres H. Neuhaus,

Scientific Reports

2018

188

Deep Learning Based on Event-Related EEG Differentiates Children with ADHD from Healthy Controls

Amirali Vahid, Annet Bluschke, Veit Roessner,

Journal of Clinical Medicine

2019

109

Applying deep learning to single-trial EEG data provides evidence for complementary theories on action control

Amirali Vahid, Moritz Mückschel, Sebastian Stober,

Communications Biology

2020

93

Training a machine learning classifier to identify ADHD based on real-world clinical data from medical records

Pavol Mikoláš, Amirali Vahid, Fabio Bernardoni,

Scientific Reports

2022

38

Conditional generative adversarial networks applied to EEG data can inform about the inter-relation of antagonistic behaviors on a neural level

Amirali Vahid, Moritz Mückschel, Sebastian Stober,

Communications Biology

2022

18

Human identification with EEG signals in different emotional states

Amirali Vahid

2016

12

The Intensity of Early Attentional Processing, but Not Conflict Monitoring, Determines the Size of Subliminal Response Conflicts

Wiebke Bensmann, Amirali Vahid, Christian Beste,

Frontiers in Human Neuroscience

2019

10

A data driven machine learning approach to differentiate between autism spectrum disorder and attention-deficit/hyperactivity disorder based on the best-practice diagnostic instruments for autism

Nicole Wolff, Gregor Kohls, Judith T. Mack,

Scientific Reports

2022

10

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