Full Text Available

Note: Clicking the button above will open the full text document at the original institutional repository in a new window.

Parkinson’s disease classification using optimized attention-based deep learning from EEG signals with interpretable sub-band topography

Saved in:
Bibliographic Details
Published in:Brain Informatics
Format: Online Article RSS Article
Published: 2026
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1869663107882680320
collection WordPress RSS
FRELIP Feed Integration
container_title Brain Informatics
description
discipline_display Psychiatry and Neurology
discipline_facet Psychiatry and Neurology
format Online Article
RSS Article
genre Journal Article
id rss_article:98712
institution FRELIP
journal_source_facet Brain Informatics
last_indexed 2026-07-03T03:34:46.276Z
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Parkinson’s disease classification using optimized attention-based deep learning from EEG signals with interpretable sub-band topography
Psychiatry and Neurology
General
Psychiatry and Neurology
sub_discipline_display General
sub_discipline_facet General
subject_display Psychiatry and Neurology
General
Psychiatry and Neurology
subject_facet Psychiatry and Neurology
General
Psychiatry and Neurology
title Parkinson’s disease classification using optimized attention-based deep learning from EEG signals with interpretable sub-band topography
title_alt Clasificación de la enfermedad de Parkinson utilizando aprendizaje profundo basado en atención optimizada a partir de señales EEG con topografía de subbandas interpretable
Classification de la maladie de Parkinson à l'aide d'un apprentissage profond optimisé basé sur l'attention à partir de signaux EEG avec topographie de sous-bandes interprétable
Classificação da doença de Parkinson usando aprendizado profundo baseado em atenção otimizada a partir de sinais de EEG com topografia de sub-bandas interpretável
title_auth Parkinson’s disease classification using optimized attention-based deep learning from EEG signals with interpretable sub-band topography
title_es_txt Clasificación de la enfermedad de Parkinson utilizando aprendizaje profundo basado en atención optimizada a partir de señales EEG con topografía de subbandas interpretable
title_fr_txt Classification de la maladie de Parkinson à l'aide d'un apprentissage profond optimisé basé sur l'attention à partir de signaux EEG avec topographie de sous-bandes interprétable
title_full Parkinson’s disease classification using optimized attention-based deep learning from EEG signals with interpretable sub-band topography
title_fullStr Parkinson’s disease classification using optimized attention-based deep learning from EEG signals with interpretable sub-band topography
title_full_unstemmed Parkinson’s disease classification using optimized attention-based deep learning from EEG signals with interpretable sub-band topography
title_pt_txt Classificação da doença de Parkinson usando aprendizado profundo baseado em atenção otimizada a partir de sinais de EEG com topografia de sub-bandas interpretável
title_short Parkinson’s disease classification using optimized attention-based deep learning from EEG signals with interpretable sub-band topography
title_sort parkinson’s disease classification using optimized attention-based deep learning from eeg signals with interpretable sub-band topography
topic Psychiatry and Neurology
General
Psychiatry and Neurology
url https://link.springer.com/article/10.1186/s40708-026-00317-x