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. 2017 Mar 3;9:6. doi: 10.3389/fnagi.2017.00006

Table 2.

Comparison of ADAS-Cog and MMSE prediction results by our proposed SMTL method and three feature selection methods: Lasso, TGL, and cFSGL, using Corr and RMSE measurement.

ADAS–Cog MMSE
Lasso TGL cFSGL SMTL Lasso TGL cFSGL SMTL
Baseline Corr 0.32 ± 0.08 0.49 ± 0.08 0.58 ± 0.08 0.77 ± 0.05 0.51 ± 0.09 0.56 ± 0.12 0.64 ± 0.08 0.75 ± 0.08
M06 Corr 0.48 ± 0.07 0.50 ± 0.07 0.59 ± 0.05 0.78 ± 0.04 0.49 ± 0.07 0.48 ± 0.10 0.63 ± 0.10 0.79 ± 0.10
M12 Corr 0.46 ± 0.12 0.52 ± 0.09 0.62 ± 0.05 0.79 ± 0.04 0.52 ± 0.06 0.57 ± 0.08 0.64 ± 0.12 0.79 ± 0.12
M24 Corr 0.57 ± 0.08 0.53 ± 0.08 0.69 ± 0.05 0.84 ± 0.04 0.61 ± 0.05 0.58 ± 0.05 0.65 ± 0.05 0.83 ± 0.06
Baseline RMSE 5.19 ± 0.33 5.53 ± 0.32 5.20 ± 0.33 3.81 ± 0.45 2.25 ± 0.20 2.30 ± 0.24 2.24 ± 0.21 1.75 ± 0.20
M06 RMSE 5.48 ± 0.62 5.90 ± 0.65 5.48 ± 0.63 4.36 ± 0.46 2.75 ± 0.31 2.85 ± 0.33 2.76 ± 0.32 2.31 ± 0.29
M12 RMSE 6.25 ± 0.58 6.74 ± 0.63 6.24 ± 0.59 4.91 ± 0.56 3.42 ± 0.49 3.59 ± 0.52 3.42 ± 0.50 2.48 ± 0.40
M24 RMSE 7.95 ± 1.20 7.81 ± 1.39 7.96 ± 1.23 6.00 ± 1.00 4.05 ± 0.58 4.48 ± 0.82 4.04 ± 0.58 3.00 ± 0.38