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    Additional file 1 of Predicting cognitive scores from wearable-based digital physiological features using machine learning: data from a clinical trial in mild cognitive impairment

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    Additional file 1: Table S1. Digital physiological features. Appendix S1. Gompertz function parameters. Appendix S2. Comparison of imputation methods. Figures S1-S3. Comparison of correlation coefficients between NTB composite scores and digital physiological features in datasets with and without imputation and using different interpolation methods. Table S2. Spearman and Pearson correlations between absolute NTB composite scores and physiological features. Table S3. Spearman and Pearson correlations between intra-individual changes in NTB composite scores and intra-individual changes in physiological features. Table S4. Linear mixed-effects regression results. Table S5. Features used in the best models predicting NTB composite scores. Figure S4. NTB composite scores: changes from baseline to post-intervention. Table S6. Mean and standard deviation of NTB composite scores at the baseline and post-intervention assessments
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