Computational and Mathematical Methods in Medicine / 2018 / Article / Tab 3 / Research Article
Linearized and Kernelized Sparse Multitask Learning for Predicting Cognitive Outcomes in Alzheimer’s Disease Table 3 Performance comparison of various methods with fusing multiple modalities data in terms of rMSE and nMSE on 10 cross validation cognitive prediction tasks.
Method ADAS MMSE FLU TRAILS ANIM A B -MTL-MRI6.494 ± 1.029 1.964 ± 0.306 4.911 ± 0.256 16.39 ± 2.906 55.82 ± 7.689 -MTL-PET6.941 ± 1.244 2.118 ± 0.298 5.192 ± 0.145 16.56 ± 3.533 56.88 ± 9.447 -MTL-MP6.219 ± 1.037 2.067 ± 0.293 4.928 ± 0.260 16.09 ± 2.768 53.70 ± 7.144 -MTL-ALL6.174 ± 0.978 2.062 ± 0.272 4.789 ± 0.206 15.97 ± 2.785 53.37 ± 7.243 -MKMTL-MRI6.369 ± 0.941 2.074 ± 0.291 4.993 ± 0.235 16.18 ± 3.089 55.95 ± 9.479 -MKMTL-PET6.812 ± 1.155 2.060 ± 0.364 5.151 ± 0.227 16.61 ± 3.588 57.85 ± 11.24 -MKMTL-MP6.112 ± 0.886 2.005 0.258 4.966 ± 0.269 16.13 ± 2.988 54.13 ± 9.450 -MKMTL-ALL5.960 ± 0.834 1.959 ± 0.256 4.821 ± 0.224 16.00 ± 3.062 53.48 ± 9.592 -MKMTL-MRI6.425 ± 0.951 1.951 ± 0.308 4.886 ± 0.264 16.11 ± 2.939 54.96 ± 7.499 -MKMTL-PET6.783 ± 1.059 2.058 ± 0.323 5.107 ± 0.258 16.52 ± 3.515 55.51 ± 9.568 -MKMTL-MP6.086 ± 0.987 1.917 ± 0.299 4.855 ± 0.249 15.95 ± 2.996 52.44 ± 8.074 -MKMTL-ALL6.034 ± 0.978 1.905 ± 0.294 4.809 ± 0.244 15.88 3.028 52.20 ± 8.120 Method RAVLT nMSE TOTAL TOT6 T30 RECOG -MTL-MRI10.18 ± 0.640 3.538 ± 0.147 3.735 ± 0.199 3.169 ± 0.306 10.24 ± 0.735 -MTL-PET10.41 ± 0.441 3.627 ± 0.140 3.796 ± 0.176 3.258 ± 0.360 10.72 ± 1.163 -MTL-MP10.01 ± 0.556 3.501 ± 0.149 3.693 ± 0.196 3.164 ± 0.314 9.710 ± 0.627 -MTL-ALL9.755 ± 0.575 3.450 0.151 3.643 ± 0.200 3.172 ± 0.313 9.525 ± 0.608 -MKMTL-MRI10.09 ± 0.605 3.532 ± 0.081 3.731 ± 0.253 3.203 ± 0.304 10.21 ± 1.019 -MKMTL-PET10.30 ± 0.436 3.592 ± 0.145 3.754 ± 0.231 3.200 ± 0.357 10.82 ± 1.455 -MKMTL-MP9.787 ± 0.375 3.471 ± 0.089 3.664 ± 0.199 3.159 ± 0.302 9.713 ± 0.968 -MKMTL-ALL9.350 ± 0.460 3.402 ± 0.030 3.604 ± 0.221 3.196 ± 0.291 9.410 ± 0.985 -MKMTL-MRI9.984 ± 0.525 3.477 ± 0.130 3.678 ± 0.204 3.143 ± 0.314 9.937 ± 0.753 -MKMTL-PET10.19 ± 0.410 3.565 ± 0.146 3.745 ± 0.212 3.191 ± 0.351 10.31 ± 1.105 -MKMTL-MP9.727 ± 0.467 3.397 ± 0.136 3.593 ± 0.162 3.112 ± 0.323 9.282 ± 0.869 -MKMTL-ALL9.561 ± 0.442 3.361 ± 0.124 3.556 ± 0.170 3.104 ± 0.327 9.160 ± 0.860