Efficient hybrid algorithm based on genetic with weighted fuzzy rule for developing a decision support system in prediction of heart diseases

摘要: In this article, the clinical decision support system is discussed under weighted fuzzy rule approach and genetic algorithm for computer-aided heart disease determination. The problem of feature selection solved by answers formulated from stochastic inquiry algorithm. this, weighed framework built application certain major highlights selected datasets. proposed adopted favorable positions strategy leaning being successful offered methodology activity. At last, risk forecasting outcomes experimentation on UCI machine learning source supercomputing techniques are assured in our enhanced essentially when contrasted with other frameworks terms sensitivity specificity, sensitivity, accuracy.