An integrated approach of block chain technology with machine learning and cloud computing for handling healthcare data

https://doi.org/10.53730/ijhs.v6nS1.6545

Authors

  • K. Shantha Shalini Research Scholar of Computer Science and Engineering Department in Vinayaka Mission’s Research Foundation, Salem
  • M. Nithya Professor and Head of Computer Science and Engineering Department in VMKV Engineering College affiliated to Vinayaka Mission’s Research Foundation, Salem

Keywords:

Smart contracts, Blockchain, Decentralized applications, Electronic Healthcare Records

Abstract

Healthcare industry has become one of the world's important sectors. It is one of the quickestand persistently growing industries. Healthcare Technology focuses mainly on patient's empowerment. Blockchain technology is offering healthier scope for accessing medical records privately. Patient confidentiality can be maintained more effectively using block chain. It is very difficult to hack the data because blockchain makes use of decentralized data storage. Nowadays machine learning is used for understanding the data and for analysing and making decisions in various sectors. It is one of the prominent techniques that are being applied in an extensive range of applications to solve a variety of complex problems. Machine learning plays a vital role in healthcare sector, by offering effective methods by saving time, effort and money. Convergence of blockchain technology with machine learning and cloud computing provides extremelyenriched functionalities and services which enables the healthcare industry to revolutionize with substantial results for medical professionals. For experimental results, Ethereum is used. In the proposed work, the patients can also get the disease details using machine learningconcept by providing their symptoms.

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Published

02-05-2022

How to Cite

Shalini, K. S., & Nithya, M. (2022). An integrated approach of block chain technology with machine learning and cloud computing for handling healthcare data. International Journal of Health Sciences, 6(S1), 7180–7190. https://doi.org/10.53730/ijhs.v6nS1.6545

Issue

Section

Peer Review Articles