A Novel deep learning framework for improving the quality of services using block chain technology

سال انتشار: 1400
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 122

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شناسه ملی سند علمی:

JR_IJNAA-12-2_116

تاریخ نمایه سازی: 11 آذر 1401

چکیده مقاله:

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.  

کلیدواژه ها:

Electronic Health Record (EHR) ، Quality of Service (QoS) ، Recurrent Neural ‎Network (RNN) ، Block chain

نویسندگان

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

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Department of IT, Annamalai University, Chidambaram, India.