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Table 12 Comparative Analysis of Weighted Associative analysis and Associative Rule Mining in predicting heart disease

From: A novel approach for heart disease prediction using strength scores with significant predictors

Research Confidence Score (%) Rules No of attributes in highest confidence rule Technique Dataset
Nahar et al. [36] 96 Chest_Pain_Type = asympt, Slope = flat, Thal = rev 3 ARM UCI
Said et al. [41] 91 Chest Pain Type = asymptomic and Thal = reversible defect 2 ARM UCI
Khare and Gupta [24] 94 Thal = reversible_defect, CP = asymptomatic, Exercise_Induced_Angina = yes 3 ARM UCI
Sonet et al. [41] 97 Lack-of-Exercise = yes, Stress = yes, BP = high, Smoking = yes, Diabetes = yes ֜ 5 ARM Data collected from 4 medical institutions (131 records)
99 Diabetes 1 ARM
Soni and Vyas [48] 79.5 NA NA WARM UCI
Soni et al. [46] 80 NA NA WARM UCI
Sundar et al. [50] 84 NA NA WARM UCI
Ibrahim & Sivabalakrishnan [18] 67 70..79- > yes 1 WARM UCI
Our Experiment (all features) 96 CP = asymptomatic Slope = flat Thal = reversable 3 WARM UCI
Our Experiment (8 Significant features) 98 CP = asymptomatic, Exang = Yes, Oldpeak = greaterThanZero, Thal = reversible 4