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Hierarchical Denoising of Ordinal Time Series of Clinical Scores.
- Source :
-
IEEE journal of biomedical and health informatics [IEEE J Biomed Health Inform] 2022 Jul; Vol. 26 (7), pp. 3507-3516. Date of Electronic Publication: 2022 Jul 01. - Publication Year :
- 2022
-
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.
Details
- Language :
- English
- ISSN :
- 2168-2208
- Volume :
- 26
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- IEEE journal of biomedical and health informatics
- Publication Type :
- Academic Journal
- Accession number :
- 35349462
- Full Text :
- https://doi.org/10.1109/JBHI.2022.3163126