Robust prediction of cognitive test scores in Alzheimer's patients

W. Izquierdo, H. Martin, M. Cabrerizo, A. Barreto, J. Andrian, N. Rishe, S. Gonzalez-Arias, D. Loewenstein, Ranjan Duara, M. Adjouadi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Predicting future cognitive status from current and past scores on objective cognitive tests and imaging measures would be useful in diagnosing Alzheimer's disease (AD) and to assess the progression of the disease. We used stochastic gradient boosting of decision trees on over 1,141 individuals whose clinical and imaging studies were available from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. The proposed method outperformed all the algorithms tested in all five cognitive scores (MMSE, CDRS, RAVLT, ADAS11 and ADAS13), outranking all other state-of-the-art algorithms in terms of both Pearson's correlation coefficient and root mean square error. All correlation measures between predicted and actual cognitive scores were higher than 0.9. Given the large number of subjects included in this study, all correlations were statistically significant. For the subset of MCI patients, we compared the proposed method with state of the art algorithms. Here, the proposed method outperformed all the algorithms tested in all five cognitive scores.

Original languageEnglish (US)
Title of host publication2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-7
Number of pages7
ISBN (Electronic)9781538648735
DOIs
StatePublished - Jul 1 2017
Event2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Philadelphia, United States
Duration: Dec 2 2017 → …

Publication series

Name2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings
Volume2018-January

Other

Other2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017
CountryUnited States
CityPhiladelphia
Period12/2/17 → …

ASJC Scopus subject areas

  • Signal Processing
  • Cardiology and Cardiovascular Medicine
  • Health Informatics
  • Clinical Neurology

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  • Cite this

    Izquierdo, W., Martin, H., Cabrerizo, M., Barreto, A., Andrian, J., Rishe, N., Gonzalez-Arias, S., Loewenstein, D., Duara, R., & Adjouadi, M. (2017). Robust prediction of cognitive test scores in Alzheimer's patients. In 2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings (pp. 1-7). (2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPMB.2017.8257059