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Table 1 Performances of ICA-based feature extraction. Mean values of sensitivity and specificity are reported as well as class probability originated from random forest voting

From: Deconvolution of transcriptomes and miRNomes by independent component analysis provides insights into biological processes and clinical outcomes of melanoma patients

Predicted variables Groups Accuracy (st.dev.) Sensitivity specificity P2PM (prob.) P4PM (prob.) P6PM (prob.) P4NS (prob.) NHEM (prob.)
Gender female: 179 0.996 (< 0.001) 0.994
0.994
female (0.73) female (0.66) male (0.79) female (0.68) female (0.67)
male: 293
Sample type primary: 105 0.871 (0.003) 0.733
0.733
primary (0.68) primary (0.55) primary (0.65) primary (0.59) meta-static (0.51)
metastatic: 367
Subtype (RNA cluster) immune: 170 0.902 (0.006) 0.877
0.945
keratin (0.64) keratin (0.48) keratin (0.61) keratin (0.64) keratin (0.55)
keratin: 102
MITF-low: 59