Multidimensional analysis and detection of informative features in human brain white matter
Fig 2
PCR-SGL accurately and interpretably predicts ALS diagnosis.
(a) Classification probabilities for ALS diagnosis, with controls on the left, patients on the right, predicted controls in blue, and predicted patients in orange. That is, orange dots on the left represent false positives, while blue dots on the right represent false negatives. We achieve 83% accuracy with an ROC AUC of 0.88. (b) PCR-SGL coefficients are presented on the core fibers of major fiber bundles. They exhibit high group sparsity and are concentrated in the FA of the corticospinal tract (CST). The brain is oriented with the right hemisphere in the foreground and anterior to the right of the page. The CSTL, CSTR, callosum forceps anterior (CFA), left arcuate (ARCL), and right arcuate (ARCR) bundles are indicated for orientation. (c) PCR-SGL identifies three portions of the CST as important, where (dashed line, right axis) has large values. These are centered around nodes 30, 65, and 90, corresponding to locations of substantial differences in FA between the ALS and control groups (shaded areas indicates standard error of the mean). (d) Bundle profiles for false positive classifications. Line colors correspond to the marker edge color in the top left plot. These individuals have reduced FA in the CST portions which SGL identified as important. Their misclassification is coherent with the feature importance and the group differences in FA. (e) Individual bundle profiles for false negative classifications. These individuals have bundle profiles which oscillate between the group means.