Uncovering the prognostic gene signatures for the improvement of risk stratification in cancers by using deep learning algorithm coupled with wavelet transform

Table 1 The detailed information of the data sets for tumor stage prediction

Cancer Type	#of all samples	#of samples		Proportion of 1/0 samples	Wavelet Function	AUC
Cancer Type	#of all samples	positive	negative	Proportion of 1/0 samples	Wavelet Function	AUC
BLCA	403	271	132	1:0.49	sym2	0.72
BRCA	1055	267	788	1:2.95	coif1	0.64
COAD	442	190	252	1:1.33	bior3.1	0.65
HNSC	430	336	94	1:0.28	db5	0.69
KIRC	524	204	320	1:1.57	db3	0.75
KIRP	259	66	193	1:2.92	bior3.1	0.83
LIHC	347	88	259	1:2.94	db3	0.63
LUAD	505	110	395	1:3.59	sym6	0.59
LUSC	492	91	401	1:4.41	coif5	0.57
SKCM	424	195	229	1:1.17	coif3	0.62
STAD	350	186	164	1:0.88	coif5	0.60
THCA	503	167	336	1:2.01	sym6	0.64

ISSN: 1471-2105