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.

Buscema, M., Vernieri, F., Massini, G., Scrascia, F., Breda, M., Rossini, P. M., Grossi, E., An improved I-FAST system for the diagnosis of Alzheimer's disease from unprocessed electroencephalograms by using robust invariant features, <<ARTIFICIAL INTELLIGENCE IN MEDICINE>>, 2015; 64 (1): 59-74. [doi:10.1016/j.artmed.2015.03.003] [http://hdl.handle.net/10807/69851]

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

Rossini, Paolo Maria;
2015

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.
Inglese
Buscema, M., Vernieri, F., Massini, G., Scrascia, F., Breda, M., Rossini, P. M., Grossi, E., An improved I-FAST system for the diagnosis of Alzheimer's disease from unprocessed electroencephalograms by using robust invariant features, <<ARTIFICIAL INTELLIGENCE IN MEDICINE>>, 2015; 64 (1): 59-74. [doi:10.1016/j.artmed.2015.03.003] [http://hdl.handle.net/10807/69851]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10807/69851
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