Hybrid approach: Predictive data mining model for Atrial Fibrillation

Hybrid approach is a technique used with the combinations of basic technologies such as scientific standards based on statistical association, Bayesian networks, machine learning technique of neural network, fuzzy logic, genetic algorithms etc. While using it there can be certain strengths and weaknesses of the approach. The medical researchers and practitioners may use this approach for the prognosis and diagnosis of their patients. This approach of predicting data mining model may help for better decision making on Atrial Fibrillation disease which increases the risk of heart diseases, stroke, or both leading causes of death. In this paper, we have designed the model which will deal the most common sustained heart rhythm disorder major cause of deaths.