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Attention-assisted hybrid 1D CNN-BiLSTM model for predicting electric field induced by transcranial...

Attention-assisted hybrid 1D CNN-BiLSTM model for predicting electric field induced by transcranial...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_c55c9fe558d84749be0c48625e89d1a6

Attention-assisted hybrid 1D CNN-BiLSTM model for predicting electric field induced by transcranial magnetic stimulation coil

About this item

Full title

Attention-assisted hybrid 1D CNN-BiLSTM model for predicting electric field induced by transcranial magnetic stimulation coil

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2023-02, Vol.13 (1), p.2494-2494, Article 2494

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Deep learning-based models such as deep neural network (DNN) and convolutional neural network (CNN) have recently been established as state-of-the-art for enumerating electric fields from transcranial magnetic stimulation coil. One of the main challenges related to this electric field enumeration is the prediction time and accuracy. Despite the low...

Alternative Titles

Full title

Attention-assisted hybrid 1D CNN-BiLSTM model for predicting electric field induced by transcranial magnetic stimulation coil

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_c55c9fe558d84749be0c48625e89d1a6

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_c55c9fe558d84749be0c48625e89d1a6

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-023-29695-6

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