Diagnosing the Stage of Hepatitis C Using Machine Learning

<table class="table-group" id="tab6"><tr><td><table class="table"><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr class="thead"><td class="align_center" colspan="2"> </td><td class="align_center">Samples [#]</td><td class="align_center">Precision (%)</td><td class="align_center">Miss rate (%)</td><td class="align_center">MSE (%)</td></tr><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr><td class="align_left" rowspan="2">Proposed IHSDS</td><td class="align_center">Training</td><td class="align_center">969</td><td class="align_center">98.89</td><td class="align_center">1.11</td><td class="align_center"><span style="width: 77.1798ptpx;"><svg height="11.9413pt" id="M18" style="vertical-align:-0.3499002pt" version="1.1" viewbox="-0.0498162 -11.5914 77.1798 11.9413" width="77.1798pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M285 378C315 398 338 416 353 432C373 451 384 474 384 503C384 579 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<div>Performance evaluation of the proposed IHSDS during training and validation.</div>

Journal of Healthcare Engineering

Diagnosing the Stage of Hepatitis C Using Machine Learning

Table 6