Author

Foroogh Shamsi

Rutgers, The State University of New JerseyORCID 0000-0002-1869-4392Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Assay:electronic health records· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Ali HaddadiD· 1 shared Laleh NajafizadehiD· 1 shared

Activity by Year

2020-2020 · peak 1/yr

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2 top collaborators · 1 mutual co-author link

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1 shared paperNeuroscience

Ali HaddadORCID

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1 paper

Recent·Most cited

NeuroscienceJournal of Neural EngineeringPeer-reviewedNov 27, 2020

Early Classification of Motor Tasks Using Dynamic Functional Connectivity Graphs from EEG

Foroogh Shamsi, Ali Haddad, Laleh Najafizadeh

This paper introduces a method to classify motor tasks from EEG signals with high accuracy using short recording intervals, achieving 85.32% accuracy within 500 ms.

45 citations

electronic health recordsmachine learning (classical)