Author

Ahmadreza Keihani

Tehran University of Medical SciencesORCID 0000-0001-6278-3854Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:electronic health records· 2 Organism:human· 2 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Adenauer Girardi CasaliiD· 1 shared Amin MahnamiD· 1 shared Amir Homayoun Jafari‬iD· 1 shared Elham ShamsiiD· 1 shared Fabio FerrarelliiD· 1 shared Francesco Luciano DonatiiD· 1 shared John C. RothwelliD· 1 shared Lorenzo RocchiiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperNeuroscience

Adenauer Girardi CasaliORCID

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2 papers

Recent·Most cited

NeuroscienceNeuroImagePeer-reviewedFeb 12, 2026

Recognizing EEG responses to active TMS vs. sham stimulations in different TMS-EEG datasets: a machine learning approach

Ahmadreza Keihani, Francesco Luciano Donati, Simone Russo…·Fabio Ferrarelli

This study uses a BiLSTM machine learning model to distinguish TMS-evoked EEG responses from sham stimulations across multiple datasets, achieving high accuracy with few trials.

3 citationstop 3%

humanelectronic health records

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NeurosciencebioRxivPreprintSep 7, 2020

Introducing Rhythmic Sinusoidal Amplitude-Modulated Auditory Stimuli with Multiple Message Frequency Coding for Fatigue Reduction in Normal Subjects: An EEG Study

Elham Shamsi, Zahra Shirzhiyan, Ahmadreza Keihani…·Amir Homayoun Jafari‬

This study introduces novel rhythmic auditory stimuli for BCIs, showing they improve classification accuracy and reduce user fatigue compared to simple stimuli.

DOI 10.1101/663344

humanelectronic health records

𝕏 PostBluesky