An improved I-FAST system for the diagnosis of Alzheimer's disease from unprocessed electroencephalograms by using robust invariant features

Paolo Maria Rossini, Massimo Buscema, Fabrizio Vernieri, Giulia Massini, Federica Scrascia, Marco Breda, Enzo Grossi

Risultato della ricerca: Contributo in rivistaArticolo in rivista

19 Citazioni (Scopus)

Abstract

This paper proposes a new, complex algorithm for the blind classification of the original electroencephalogram (EEG) tracing of each subject, without any preliminary pre-processing. The medical need in this field is to reach an early differential diagnosis between subjects affected by mild cognitive impairment (MCI), early Alzheimer's disease (AD) and the healthy elderly (CTR) using only the recording and the analysis of few minutes of their EEG.
Lingua originaleEnglish
pagine (da-a)59-74
Numero di pagine16
RivistaArtificial Intelligence in Medicine
Volume64
DOI
Stato di pubblicazionePubblicato - 2015

Keywords

  • Alzheimer's disease
  • Electroencephalogram
  • Implicit function as squashing time
  • Mild cognitive impairment
  • Multi scale ranked organizing maps
  • Training with input selection and testing

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