An evaluation of measures to dissociate language and communication disorders from healthy controls using machine learning techniques

Gaspers J, Thiele K, Cimiano P, Foltz A, Stenneken P, Tscherepanow M (2012)
In: Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium. ACM: 209-218.

Konferenzbeitrag | Veröffentlicht | Englisch
 
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Abstract / Bemerkung
Reliably distinguishing patients with verbal impairment due to brain damage, e.g. aphasia, cognitive communication disorder (CCD), from healthy subjects is an important challenge in clinical practice. A widely-used method is the application of word generation tasks, using the number of correct responses as a performance measure. Though clinically well-established, its analytical and explanatory power is limited. In this paper, we explore whether additional features extracted from task performance can be used to distinguish healthy subjects from aphasics or CCD patients. We considered temporal, lexical, and sublexical features and used machine learning techniques to obtain a model that minimizes the empirical risk of classifying participants incorrectly. Depending on the type of word generation task considered, the exploitation of features with state-of-the-art machine learning techniques outperformed the predictive accuracy of the clinical standard method (number of correct responses). Our analyses confirmed that number of correct responses is an adequate measure for distinguishing aphasics from healthy subjects. However, our additional features outperformed the traditional clinical measure in distinguishing patients with CCD from healthy subjects: The best classification performance was achieved by excluding number of correct responses. Overall, our work contributes to the challenging goal of distinguishing patients with verbal impairments from healthy subjects.
Stichworte
aphasia; Machine learning; word generation tasks; cognitive communication disorder
Erscheinungsjahr
2012
Titel des Konferenzbandes
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Seite(n)
209-218
Konferenz
2nd ACM SIGHIT International Health Informatics Symposium
Konferenzort
Miami, Florida, USA
Konferenzdatum
2012-01-28 – 2012-01-30
ISBN
978-1-4503-1366-7
Page URI
https://pub.uni-bielefeld.de/record/2329837

Zitieren

Gaspers J, Thiele K, Cimiano P, Foltz A, Stenneken P, Tscherepanow M. An evaluation of measures to dissociate language and communication disorders from healthy controls using machine learning techniques. In: Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium. ACM; 2012: 209-218.
Gaspers, J., Thiele, K., Cimiano, P., Foltz, A., Stenneken, P., & Tscherepanow, M. (2012). An evaluation of measures to dissociate language and communication disorders from healthy controls using machine learning techniques. Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium, 209-218. ACM. doi:10.1145/2110363.2110389
Gaspers, J., Thiele, K., Cimiano, P., Foltz, A., Stenneken, P., and Tscherepanow, M. (2012). “An evaluation of measures to dissociate language and communication disorders from healthy controls using machine learning techniques” in Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium (ACM), 209-218.
Gaspers, J., et al., 2012. An evaluation of measures to dissociate language and communication disorders from healthy controls using machine learning techniques. In Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium. ACM, pp. 209-218.
J. Gaspers, et al., “An evaluation of measures to dissociate language and communication disorders from healthy controls using machine learning techniques”, Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium, ACM, 2012, pp.209-218.
Gaspers, J., Thiele, K., Cimiano, P., Foltz, A., Stenneken, P., Tscherepanow, M.: An evaluation of measures to dissociate language and communication disorders from healthy controls using machine learning techniques. Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium. p. 209-218. ACM (2012).
Gaspers, Judith, Thiele, Kristina, Cimiano, Philipp, Foltz, Anouschka, Stenneken, Prisca, and Tscherepanow, Marko. “An evaluation of measures to dissociate language and communication disorders from healthy controls using machine learning techniques”. Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium. ACM, 2012. 209-218.
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2019-09-06T08:57:56Z
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