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. Author manuscript; available in PMC: 2016 Dec 12.
Published in final edited form as: Neurobiol Aging. 2016 Jul 15;46:180–191. doi: 10.1016/j.neurobiolaging.2016.07.005

Table 8.

The total MAEs of oRF-L1-soft (only baseline features), oRF-L1-soft-interp (linear interpolation), and oRF-L1-soft-long (our proposed algorithm with longitudinal data) across all the 4 future time points

Method MAE (mean ± standard deviation)
MMSE CDR-SOB CDR-GLOB ADAS-cog
oRF-L1-soft 1.796 ± 0.297 0.881 ± 0.195 0.209 ± 0.041 3.641 ± 0.589
oRF-L1-soft-interp 1.633 ± 0.263 0.793 ± 0.182 0.220 ± 0.042 3.201 ± 0.496
oRF-L1-soft-long 1.548 ± 0.214a 0.703 ± 0.160a 0.187 ± 0.035a 2.913 ± 0.404a

The best results are shown in bold.

Key: ADAS-cog, Alzheimer’s disease assessment scale–cognitive subscale; CDR-GLOB, clinical dementia rating–global; CDR-SOB, clinical dementia rating–sum of boxes; MAE, mean absolute error; MMSE, Mini-Mental State Examination; oRF-L1-soft, oblique RF with L1 and soft split.

a

Represents that the result in bold is statistically significantly better than other comparison methods (p < 0.05).