Knowledge Mining from Clinical Datasets Using Rough Sets and Backpropagation Neural Network

Table 13

Comparison of proposed system with recent works.

Author	Technique	Accuracy of dataset (%)
		Hepatitis	Breast cancer	Heart disease
Sartakhti et al. (2012) [16]	SVM-SA	96.25	—	—
Chen et al. (2011) [20]	LFDA-SVM	96.77	—	—
Çalişir and Dogantekin (2011) [21]	PCA-LSSVM	96.12	—	—
Bascil and Temurtas (2011) [26]	MLNN	91.87	—	—
Dogantekin et al. (2009) [23]	LDA-ANFIS	94.16	—	—
Polat and Güneş (2006) [27]	FS_AIRS	94.12
Zheng et al. (2014) [28]	K-SVM	—	97.38	—
Karabatak and Ince (2009) [24]	AR_NN	—	95.60	—
Shao et al. (2014) [14]	MARS-LR	—	—	83.93
Anooj (2012) [17]	Weighted fuzzy	—	—	62
Vijaya et al. (2010) [22]	Fuzzy neurogenetic	—	—	80
Kahramanli and Allahverdi (2008) [25]	ANN-FNN	—	—	87
Proposed method	RS-BPNN	97.3	98.6	90.4