Author

Neetha Das

KU LeuvenORCID 0000-0003-1301-1043Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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

Frequent Co-Authors

Alexander BertrandiD· 2 shared Tom FrancartiD· 2 shared Amir H. AnsariiD· 1 shared Jonas VanthornhoutiD· 1 shared Lucas DeckersiD· 1 shared Servaas VandecappelleiD· 1 shared

Activity by Year

2019-2021 · peak 1/yr

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6 top collaborators · 12 mutual co-author links

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2 shared papersNeuroscience

Alexander BertrandORCID

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2 papers

Recent·Most cited

NeuroscienceeLifePeer-reviewedApr 30, 2021

EEG-based detection of the locus of auditory attention with convolutional neural networks

Servaas Vandecappelle, Lucas Deckers, Neetha Das…·Tom Francart

This study uses convolutional neural networks to detect auditory attention locus (left/right) from EEG signals in multi-speaker scenarios, achieving 81% median accuracy within 1-2 seconds.

152 citationstop 1%

humanelectronic health records

𝕏 PostBluesky

NeuroscienceNeuroImagePeer-reviewedSep 20, 2019

Stimulus-aware spatial filtering for single-trial neural response and temporal response function estimation in high-density EEG with applications in auditory research

Neetha Das, Jonas Vanthornhout, Tom Francart, Alexander Bertrand

This paper introduces a stimulus-aware spatial filtering method for improving neural response and temporal response function estimation in EEG data, showing improved performance over standard approaches.

24 citations

electronic health recordsstatistical model

𝕏 PostBluesky