Neural Fuzzy Hybrid Rule-Based Inference System with Test Cases for Prediction of Heart Attack Probability

Table 5

Model comparison with existing similar research work.

Author name	Proposed approach	Classification technique	Prediction rate in percentage
Samuel et al. [15]	Hybrid system which combines fuzzy analytic hierarchy process (fuzzy AHP) technique and ANN	ANN and fuzzy AHP	Accuracy: 91.1%
Aghamohammadi et al. [13]	Genetic algorithm (GA) and adaptive neural fuzzy inference system (ANFIS)	ANFIS	Accuracy: 84.43%, sensitivity: 91.1504%, specificity: 79.1667%
Li et al. [35]	Combination of FuzzyGMEn-generated DDM and CNN (Inception_v4 model)	CNN	Accuracy: 81.85%
Ziasabounchi and Askerzade [14]	ANFIS-based classification model	ANFIS	Accuracy: 92.30%
Abushariah et al. [32]	Artificial neural network (ANN) and adaptive neuro-fuzzy inference systems (ANFIS)	ANN, ANFIS	Accuracy: 87.04%
Rahul, Henge and Sharma	This study	Hybrid GANN + fuzzy inference system	Accuracy: 94%