Why the study?
Does a machine learning approach for analyzing EEG signals improve the diagnosis of Alzheimer's disease?
Does a machine learning approach for analyzing EEG signals improve the diagnosis of Alzheimer's disease?
Machine learning algorithms applied to EEG features offer a promising method for the early and accurate diagnosis of Alzheimer's disease.
Should not yet alter AD diagnostic pathways; leaves open prospective validation in larger cohorts.
In order to have the greatest treatment impact the early and accurate diagnose of Alzheimer’s disease (AD) is essential. In this paper we present a method for analyzing EEG signals with machine learning approach in order to diagnose AD. We show how to extract features out of EEG recordings to be used with a machine learning algorithm for the induction of AD classification model. The obtained results are very promising.DOI: http://dx.doi.org/10.5755/j01.eee.18.8.2627
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Vili Podgorelec (2012) studied this question.
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