Volume 8 Issue 2 - March 2017

  • 1. Cardiovascular disease prediction using genetic algorithm and neuro-fuzzy system

    Authors : Sneha Nikam, Priyanshi Shukla, Megh Shah

    Pages : 104-110

    DOI : http://dx.doi.org/10.21172/1.82.016

    Keywords : Heart diseases risk factors, Prediction and Diagnosis systems, Genetic algorithm, NFS

    Abstract :

    Cardiovascular disease (CVD) is related to heart and a major cause of morbidity and transience in the modern society. Diagnosis of cardiovascular disease using various medical tests is an important but complicated task which should be performed accurately. Hence a powerful tool in the prediction of heart disease with lower cost has become the need of time. A very scarce number of the systems predict heart diseases based on risk factors such as age, family history, diabetes, hypertension, high cholesterol, tobacco smoking, alcohol intake, obesity or physical inactivity, etc. Heart disease patients have lot of these visible risk factors in common which can be used very effectively for diagnosis. System based on such risk factors would not only help medical professionals but it would give patients a warning about the probable presence of heart disease even before he visits a hospital. In this paper, we will apply NFS to the dataset which is nothing but the risk factors, for prediction and training of network will be done using back propagation algorithm and weight optimization will be done by genetic algorithm. The NFS combines neuro adaptive capability and fuzzy logic reasoning for prediction

    Citing this Journal Article :

    Sneha Nikam, Priyanshi Shukla, Megh Shah, "Cardiovascular disease prediction using genetic algorithm and neuro-fuzzy system", https://www.ijltet.org/journal_details.php?id=911&j_id=3665, Volume 8 Issue 2 - March 2017, 104-110, #ijltetorg