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Table 6 Machine learning results for local clinical data

From: Comparison of machine learning and semi-quantification algorithms for (I123)FP-CIT classification: the beginning of the end for semi-quantification?

Method number Feature No. PCs Kernel Mean accuracy SD Sensitivity SD Specificity SD
ML 1 PCs 3 Linear 0.91 0.05 0.93 0.05 0.88 0.10
ML 2 PCs 5 Linear 0.92 0.05 0.94 0.06 0.88 0.10
ML 3 PCs 10 Linear 0.91 0.05 0.93 0.06 0.86 0.10
ML 4 PCs 15 Linear 0.89 0.05 0.92 0.06 0.83 0.11
ML 5 PCs 20 Linear 0.89 0.05 0.92 0.07 0.83 0.12
ML 6 PCs 3 RBF 0.91 0.05 0.91 0.07 0.89 0.09
ML 7 PCs 5 RBF 0.91 0.06 0.92 0.06 0.89 0.10
ML 8 PCs 10 RBF 0.90 0.05 0.91 0.07 0.88 0.09
ML 9 PCs 15 RBF 0.89 0.05 0.91 0.07 0.87 0.10
ML 10 PCs 20 RBF 0.90 0.05 0.90 0.07 0.89 0.10
ML 11 Voxels   Linear 0.88 0.05 0.91 0.06 0.84 0.11
ML 12 SBRs   Linear 0.89 0.05 0.92 0.06 0.82 0.10
ML 13 SBRs   RBF 0.89 0.06 0.91 0.07 0.85 0.10