A Frame Work for Hospital Readmission Based on Deep Learning Approach and Naive Bayes Classification Model

Received: 18 October 2018 Accepted: 3 February 2019 From the last few years has seen an eruption in the quantity of digital data stored in electronic health records (EHR). Presently the most difficult thing in world that was facing by patients and doctors was when to join hospital. And how to start treatment for patent. If a person was sick, he wants to go which hospital and met which kind of doctor for his problem. When a doctor diagnoses a person for some decease he needs his past medical history. Previously, these medical prescriptions were written on papers. But these papers are no longer available. Presently, the better choice is Electronic health records (EHR). But EHR data is a heterogeneous in nature, in order to process heterogeneous data we use deep learning based feature extraction method, and for predation we use navie basian classifier to make prediction. Here in this paper we propose a frame work based on VAR and Skipgram method to take features using those feature we use basian classification to predict the readmission into hospital.