Abstract:
In recent years, Mild Cognitive Impairment (MCI) has received a great deal of attention, as it may represent a pre-clinical state of Alzheimer's disease (AD). In the distinction between healthy elderly (CTL) and MCI patients, automated discourse analysis tools have been applied to narrative transcripts in English and in Brazilian Portuguese. However, the absence of sentence boundary segmentation in transcripts prevents the direct application of methods that rely on these marks for the correct use of tools, such as taggers and parsers. To our knowledge, there are only a few studies evaluating automatic sentence segmentation in transcripts of neuropsychological tests. The purpose of this study is to investigate the impact of the automatic sentence segmentation method DeepBond on nine syntactic complexity metrics extracted of transcripts of CTL and MCI patients.
Keywords:
Clinical diagnosis; Mild cognitive impairment; Automatic sentence segmentation; Syntactic complexity metrics; Automated discourse analysis tools
