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Authors: Elif Eyigöz ; Guillermo Cecchi and Ravi Tejwani

Affiliation: IBM Research, United States

Keyword(s): Automatic Prediction of MMSE, Syntactic Complexity, Cognitive Impairments.

Abstract: Assessment of cognitive impairments is of social and clinical importance for vulnerable populations, such as elderly, athletes and soldiers, who are prone to falling victim to cognitive impairments. This paper presents ongoing work for developing an application that predicts the neurological state of users with the state-of-the art performance through analyzing the structural complexity of users' utterances. We present a novel method that estimates the neurological state of users with Pearson correlation of 0.66 with respect to the Mini-mental state exam score. Unlike previous work, our method does not depend on assumptions of relating linguistics representations to human language-processing capabilities, but discovers the discriminative patterns automatically.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Eyigöz, E.; Cecchi, G. and Tejwani, R. (2018). Predicting Cognitive Impairments with a Mobile Application. In Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 2: NLPinAI; ISBN 978-989-758-275-2; ISSN 2184-433X, SciTePress, pages 683-692. DOI: 10.5220/0006734006830692

@conference{nlpinai18,
author={Elif Eyigöz. and Guillermo Cecchi. and Ravi Tejwani.},
title={Predicting Cognitive Impairments with a Mobile Application},
booktitle={Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 2: NLPinAI},
year={2018},
pages={683-692},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006734006830692},
isbn={978-989-758-275-2},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 2: NLPinAI
TI - Predicting Cognitive Impairments with a Mobile Application
SN - 978-989-758-275-2
IS - 2184-433X
AU - Eyigöz, E.
AU - Cecchi, G.
AU - Tejwani, R.
PY - 2018
SP - 683
EP - 692
DO - 10.5220/0006734006830692
PB - SciTePress