Automated Classification of Cognitive Decline and Probable Alzheimer's Dementia Across Multiple Speech and Language Domains.

Background: Decline in language has emerged as a new potential biomarker for the early detection of Alzheimer's disease (AD). It remains unclear how sensitive language measures are across different tasks, language domains, and languages, and to what extent changes can be reliably detected in early stages such as subjective cognitive decline (SCD) and mild cognitive impairment (MCI).

Method: Using a scene construction task for speech elicitation in a new Spanish/Catalan speaking cohort ( = 119), we automatically extracted features across seven domains, three acoustic (spectral, cepstral, and voice quality), one prosodic, and three from text (morpholexical, semantic, and syntactic).

A classification of user-generated content into consumer decision journey stages.

In the last decades, the availability of digital user-generated documents from social media has dramatically increased. This massive growth of user-generated content has also affected traditional shopping behaviour. Customers have embraced new communication channels such as microblogs and social networks that enable them not only just to talk with friends and acquaintances about their shopping experience, but also to search for opinions expressed by complete strangers as part of their decision making processes.