Diagnosing the Stage of Hepatitis C Using Machine Learning

Table 7

Comparison of the proposed model with previously presented models using validation precision.

Literature	Dataset description	Precision (%)	Miss rate (%)
Extreme Gradient Boosting [10]	HCV Egyptian cohort dataset (1385 samples of 6 features are used)	81.00	19.00
Random Forest [14]	HCV dataset by Clinical Research Committee of Second Xiangya Hospital, Central South University (920 samples of 9 features are used)	83.00	17.00
Support Vector Machine (SVM) with linear kernel [11]	18 liver biopsy images of the trichrome (TC) stained slides	85.60	14.40
Random Forest [13]	Dataset of children attending hospital outpatient clinic (166 samples of 14 features are used)	90.30	9.70
Proposed IHSDS	HCV Egyptian cohort dataset (1385 samples of 18 features are used)	94.44	5.56