BioMed Research International / 2018 / Article / Tab 7 / Research Article
Predicting Advanced Prostate Cancer from Modeling Early Indications in Biopsy and Prostatectomy Samples via Transductive Semi-Supervised Survival Analysis Table 7 Weights of features in models with multimodal characteristics from biopsy data.
ā Cox Model Cox Model with Transduction SVRc SVRc with Transduction Feature Original Weight Normalized Weight Original Weight Normalized Weight Original Weight Normalized Weight Original Weight Normalized Weight PSA 1.715 1.000 1.720 1.000 -60.799 -5.430 -62.229 -6.859 Dominant Biopsy Gleason Grade 0.565 0.329 0.467 0.272 -21.025 -1.878 -23.007 -2.536 Biopsy Gleason Sum 0.476 0.278 0.586 0.341 -22.943 -2.049 -22.912 -2.525 AR Expression 0.251 0.146 0.185 0.108 -18.932 -1.691 -19.903 -2.194 Nuclear Morphology -0.228 -0.133 -0.263 -0.153 -0.866 -0.077 -0.001 0.0001 Ki67+ Area 0.885 0.516 0.793 0.461 -28.498 -2.545 -28.366 -3.127 Luminal Area -0.171 -0.100 -0.159 -0.093 11.197 1.000 9.073 1.000 Epithelial Cells Infiltration -0.127 -0.074 -0.161 -0.094 -2.226 -0.199 -3.040 -0.335 Glandular Size 0.088 0.052 0.019 0.011 -9.765 -0.872 -8.777 -0.967