In the present study, we analyzed written samples obtained from Greek native speakers diagnosed w... more In the present study, we analyzed written samples obtained from Greek native speakers diagnosed with Alzheimer's Disease (AD) in mild and moderate stages and from age-matched cognitively normal controls (NC). We adopted a computational approach for the comparison of morpho-syntactic complexity and lexical variety in the samples. We used text classification approaches to assign the samples to one of the two groups. The classifiers were tested using various morphosyntactic and lexical features. The proposed method excels in discerning AD patients in mild and moderate stages from NC, leading to an in depth understanding of language deficits in this neurodegenerative disease.
In the present study, we analyzed written samples obtained from Greek native speakers diagnosed w... more In the present study, we analyzed written samples obtained from Greek native speakers diagnosed with Alzheimer's in mild and moderate stages and from age-matched cognitively normal controls (NC). We adopted a computational approach for the comparison of morpho-syntactic complexity and lexical variety in the samples. We used text classification approaches to assign the samples to one of the two groups. The classifiers were tested using various features: morpho-syntactic and lexical characteristics. The proposed method excels in discerning AD patients in mild and moderate stages from NC leading to the in-depth understanding of language deficits.
Although language changes in Alzheimer's Disease (hence, AD) have been well documented, there are... more Although language changes in Alzheimer's Disease (hence, AD) have been well documented, there are several limitations in the language investigation of these groups. A primary limitation is that the language analysis of these groups is manual, a process which is time consuming and in most of the cases subjective. The current study adopts a computational approach based on machine learning (hence, ML) to characterize language samples from people with AD in terms of linguistically defined criteria.
Poster presented at the Alzheimer's Association International Conference in Chicago, U.S.A. (22-2... more Poster presented at the Alzheimer's Association International Conference in Chicago, U.S.A. (22-26 July (2018)
In the present study, we analyzed written samples obtained from Greek native speakers diagnosed w... more In the present study, we analyzed written samples obtained from Greek native speakers diagnosed with Alzheimer's Disease (AD) in mild and moderate stages and from age-matched cognitively normal controls (NC). We adopted a computational approach for the comparison of morpho-syntactic complexity and lexical variety in the samples. We used text classification approaches to assign the samples to one of the two groups. The classifiers were tested using various morphosyntactic and lexical features. The proposed method excels in discerning AD patients in mild and moderate stages from NC, leading to an in depth understanding of language deficits in this neurodegenerative disease.
In the present study, we analyzed written samples obtained from Greek native speakers diagnosed w... more In the present study, we analyzed written samples obtained from Greek native speakers diagnosed with Alzheimer's in mild and moderate stages and from age-matched cognitively normal controls (NC). We adopted a computational approach for the comparison of morpho-syntactic complexity and lexical variety in the samples. We used text classification approaches to assign the samples to one of the two groups. The classifiers were tested using various features: morpho-syntactic and lexical characteristics. The proposed method excels in discerning AD patients in mild and moderate stages from NC leading to the in-depth understanding of language deficits.
Although language changes in Alzheimer's Disease (hence, AD) have been well documented, there are... more Although language changes in Alzheimer's Disease (hence, AD) have been well documented, there are several limitations in the language investigation of these groups. A primary limitation is that the language analysis of these groups is manual, a process which is time consuming and in most of the cases subjective. The current study adopts a computational approach based on machine learning (hence, ML) to characterize language samples from people with AD in terms of linguistically defined criteria.
Poster presented at the Alzheimer's Association International Conference in Chicago, U.S.A. (22-2... more Poster presented at the Alzheimer's Association International Conference in Chicago, U.S.A. (22-26 July (2018)
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