A Manjula

Publications

• Review Article   
  Predicting heart disease using machine learning and IoT techniques
  Author(s): N Divya*, Md Riyazuddin, Abdul Ahad, Sridhar Reddy Vulapula, A Manjula and Mohd Sirajuddin
  
  Nowadays, there is an increase in heart disease in all age groups in society. It is therefore necessary to set up a machine learning system in order to be able to detect and prevent indications of heart disease at an early stage. There must also be a mechanism in place that is handy and at the same time capable of being trusted. Thus, we propose to create an application that can predict the potential for heart disease given basic symptoms such as age, gender, ECG, heart rate, chest pain, cholesterol, blood pressure, blood sugar. The method will use various models trained using machine learning algorithms such as the support vector machine, the Naïve Bayes classifier and the decision tree. The accuracy of the method will be measured and distinguished in order to select the best model for estimating heart disease. Latest advances in online healthcare can be used for IoT and sensing.. Read More»
  

  Abstract HTML PDF