a novel deep learning framework for improving the quality of services using block chain technology

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.