Breast Cancer Classification Using FCN and Beta Wavelet Autoencoder

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left"> </td><td class="align_center"> </td><td class="align_center">Benign</td><td class="align_center">Malignant</td><td class="align_center">Normal</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left" rowspan="3">Predicted</td><td class="align_center">Benign</td><td class="align_center">473</td><td class="align_center">41</td><td class="align_center">0</td></tr><tr><td class="align_center">Malignant</td><td class="align_center">30</td><td class="align_center">555</td><td class="align_center">0</td></tr><tr><td class="align_center">Normal</td><td class="align_center">0</td><td class="align_center">0</td><td class="align_center">500</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>C<small class="sc"></small>onfusion matrix.</div>

Computational Intelligence and Neuroscience

tab2

Table 2

Table 2: Breast Cancer Classification Using FCN and Beta Wavelet Autoencoder 