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Table 3 Three subsets of feature methods of the training group predicting TNBC

From: Application of mammography-based radiomics signature for preoperative prediction of triple-negative breast cancer

Feature selection method

Parameter

Fisher

WavEnHH_s-3, WavEnLH_s-4, WavEnHL_s-4, WavEnHL_s-2, WavEnLH_s-3, GrMean, S(0,1) SumAverg, S(1,1) SumAverg, S(1,-1) SumAverg, S(2,0) SumAverg

POE + ACC

WavEnLH_s-4, Kurtosis, Perc.01%, Vertl_LngREmph, WavEnHH_s-5, Teta4, WavEnHL_s-5, 135dr_ShrtREmp, GrKurtosis, WavEnHH_s-1

MI

WavEnLL_s-2, WavEnLL_s-1, 135dr_Fraction, 135dr_LngREmph, WavEnLH_s-4, S(0,2) SumOfSqs, S(1,0) SumOfSqs, S(1,1) SumOfSqs, S(2,0) SumOfSqs, S(2,2) SumOfSqs

  1. Fisher: Fisher parameter method; POE + ACC: Classification error rate combined average correlation coefficient method; MI: Related Information Measurement; Wavelet transform: WavEnHH_s-3,WavEnLH_s-4,WavEnHL_s-4, WavEnHL_s-2, WavEnLH_s-3, WavEnHH_s-5, WavEnHL_s-5, WavEnHH_s-1, WavEnLL_s-2, WavEnLL_s-1; Gradient model: GrMean, 135dr_ShrtREmp, GrKurtosis, 135dr_Fraction, 135dr_LngREmph; Gray Level Co-occurrence Matrix: S(0,1) SumAverg, S(1,1) SumAverg, S(1,-1) SumAverg, S(2,0) SumAverg, S(0,2) SumOfSqs, S(1,0) SumOfSqs, S(1,1) SumOfSqs, S(2,0) SumOfSqs, S(2,2) SumOfSqs; Histogram: Kurtosis, Perc.01%; Run matrix: Vertl_LngREmph; Autoregressive model: Teta4
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BMC Medical Imaging

ISSN: 1471-2342

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