Predictive analytics: A case study in healthcare for lifestyle diseases

  • Harsh Vardhan Mishra Noida Institute of Engineering and Technology, Greater Noida, UP, India
  • Somesh Kumar Moradabad Institute of Technology, Moradabad, UP, India


In healthcare the prediction of lifestyle diseases, using machine learning algorithms, is a big challenge. Lifestyle diseases include hypertension, obesity, cardiovascular diseases, diabetes etc. Some of these in turn to fatal problems. For example, When pancreas in the body are not able to produce required amount of insulin in the body diabetes occurs and it starts damaging the retina of the human eye and thus affecting the vision. Depending upon the severity there are multiple stages of Diabetic Retinopathy (DR). Predictive analytics can be used to overcome this problem and thus using the help of convolution neural network (CNN), one can detect the stages of severity for Diabetic Retinopathy. Predictive analytics is a statistical technique to find unknown data from the known data set by using various tools and algorithms available in data mining, statistical modeling, artificial intelligence, machine learning and deep learning. Similar predictive models can be applied in numerous lifestyle diseases.