Research In Cardiovascular Diseases And Its Complications Based On Bayesian Network

Cardiovascular diseases have become one of the most serious diseases to threaten the human's life and health in the 21st century,because of its high morbidity and lethality.The patients can suffer from other chronic diseases while they have cardiovascular diseases,so it is significant to study the causalities among the diseases.Neverthless,the research on causalities between each pair of the diseases takes exponential complexity and cannot illuminate the causalities explicitly.Bayesian Network(BN)is a probabilistic graphical model that encodes complex probability distributions among random variables by directed acyclic graph,which features conciseness and bi-directional inference.The article applies Bayesian Network to build the causal network of cardiovascular diseases and other chronic diseases,selects the optimal result from the networks generated by three kinds of BN learning methods in terms of structural complexity,overall score and conditional independence test,and reasoning the causalities based on this result.The consequences show that BN has advantages in causal inference among cardiovascular diseases and other chronic diseases.The results have positive effect on the prevention and clinical treatment of diseases.