Hierarchical Denoising of Ordinal Time Series of Clinical Scores.

Koss, Jonathan; Tinaz, Sule; Tagare, Hemant D · IEEE J Biomed Health Inform · 2022

basic_science · Level V

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Abstract

Clinical scores (disease rating scales) are ordinal in nature. Longitudinal studies which use clinical scores produce ordinal time series. These time series tend to be noisy and often have a short-duration. This paper proposes a denoising method for such time series. The method uses a hierarchical approach to draw statistical power from the entire population of a study's patients to give reliable, subject-specific results. The denoising method is applied to MDS-UPDRS motor scores for Parkinson's disease.

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