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Parameters of stochastic models for electroencephalogram data as biomarkers for child’s neurodevelopment after cerebral malaria

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  • Maria A. Veretennikova

    (Department of Statistics and Data Analysis, Faculty of Economic Science, National Research University, Higher School of Economics)

  • Alla Sikorskii

    (Michigan State University)

  • Michael J. Boivin

    (Michigan State University)

Abstract

The objective of this study was to test statistical features from the electroencephalogram (EEG) recordings as predictors of neurodevelopment and cognition of Ugandan children after coma due to cerebral malaria. The increments of the frequency bands of EEG time series were modeled as Student processes; the parameters of these Student processes were estimated and used along with clinical and demographic data in a machine-learning algorithm for the prediction of children’s neurodevelopmental and cognitive scores 6 months after cerebral malaria illness. The key innovation of this work is in the identification of stochastic EEG features that can serve as language-independent markers of the impact of cerebral malaria on the developing brain. The results can enhance prognostic determination of which children are in most need of rehabilitative interventions, which is especially important in resource-constrained settings such as sub-Saharan Africa.

Suggested Citation

  • Maria A. Veretennikova & Alla Sikorskii & Michael J. Boivin, 2018. "Parameters of stochastic models for electroencephalogram data as biomarkers for child’s neurodevelopment after cerebral malaria," Journal of Statistical Distributions and Applications, Springer, vol. 5(1), pages 1-12, December.
  • Handle: RePEc:spr:jstada:v:5:y:2018:i:1:d:10.1186_s40488-018-0086-7
    DOI: 10.1186/s40488-018-0086-7
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    References listed on IDEAS

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    1. Claudia Kirch & Birte Muhsal & Hernando Ombao, 2015. "Detection of Changes in Multivariate Time Series With Application to EEG Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1197-1216, September.
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