Applying Machine Learning Algorithms to Develop a Universal Cardiovascular Disease Prediction System

  • Ekta Maini
  • Bondu Venkateswarlu
  • Arbind Gupta
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 26)


The biggest reason that accounts to the maximum number of death worldwide are cardiovascular disease. i.e. a huge section of people die due to Cardiovascular (CVDs) than from some other reason. According to WHO survey, nearly 80% of CVD deaths take place in underdeveloped or developing middle-income countries like India. Therefore, there is a great need to predict the disease at a premature phase to combat with this alarming situation. As tremendous quantity of data is generated by healthcare industry the data mining techniques can be efficiently explored to identify hidden patterns and interesting knowledge that may help in effective and efficient decision making. Purpose of this paper is to recommend development of a cloud based decision support system for the prediction and diagnosis of cardiovascular diseases using the methods of machine leaning. This cloud based solution will aid in making healthcare affordable in middle income groups.


Decision support system Data mining Algorithms for machine learning Rural health care Cloud computing Affordable healthcare 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Dayananda Sagar UniversityBengaluruIndia
  2. 2.Dayananda Sagar College of EngineeringBengaluruIndia

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