Document Type : Research Paper

Authors

• P Parthiban ¹
• K Santhosh Kumar ²

¹ Department of CSE, IFET Colleg of Engineering, Villupuram, India.

² Department of IT, Annamalai University, Chidambaram, India.

Abstract

Electronic Health Record (EHR) holds immensely sensitive information and consisting of ‎crucial data related to the patients.  Storing and organizing such data is highly arduous task.  ‎Researches still going on to improve the Quality of Service (QOS) of such data. Existing ‎study focused only on improving the system throughput, privacy and latency issues.  But they ‎did not tend to scrutinize the scalability and privacy of such data records.  In this paper, we ‎propose a novel deep learning framework to improve the Quality of Service using block chain ‎technology.  Initially the data is classified into high priority and low priority based on its ‎nature by using Recurrent Neural Network (RNN).  Then, the classified high priority data is ‎further allowed to each block of a block chain and the low priority data is stored and ‎maintained as log file. Finally, the results are compared based on the evaluation metrics ‎which demonstrates our proposed novel deep learning framework achieves better accuracy.
 

Keywords

• Electronic Health Record (EHR)
• Quality of Service (QOS)
• Recurrent Neural ‎Network (RNN)
• Block chain