@inProceedings{themistocleous-etal-2020-automated-305223, title = {Automated speech analysis improves MCI diagnosis}, abstract = {Mild Cognitive Impairment (MCI) is a condition characterized by cognitive decline greater than expected for an individual's age and education level. In this study, we are investigating whether acoustic properties of speech production can improve the classification of individuals with MCI from healthy controls augmenting the Mini Mental State Examination, a traditional screening tool, with automatically extracted acoustic information. We found that just one acoustic feature, can improve the AUC score (measuring a trade-off between sensitivity and specificity) from 0.77 to 0.89 in a boosting classification task. These preliminary results suggest that computerized language analysis can improve the accuracy of traditional screening tools}, booktitle = {Proceedings of the 11th Experimental Linguistics Conference (ExLing)}, author = {Themistocleous, Charalambos and Eckerström, Marie and Kokkinakis, Dimitrios}, year = {2020}, }