Smart Detection of Cardiovascular Disease Using Gradient Descent Optimization

  • Kausar Parveen
  • Maryam Daud
  • Shahan Yamin Siddiqu
Keywords: Cardiovascular; smart detection; gradient descent optimization; GDO; SDCD-GDO.

Abstract

The Internet of Medical Things (IoMT) is the networking of health things or equipment that communicate data over the internet without the need for human involvement in the healthcare field. A large quantity of data is collected from numerous sensors in the health field, and it is all transferred and stored on the cloud. This data is growing bigger here all time, and it's becoming increasingly challenging to secure it on the cloud with real-time storage and computing. Data security problem can be addressed with the aid of machine algorithms and fog computing. For data security in IoMT gadgets correspondence in an intelligent fashion, an intelligent encryption algorithm (IEA) is proposed using blockchain technology in cloud based system framework (CBSF). It is applied on patient’s database to provide immutable security, tampering prevention and transaction transparency at the fog layer in IoMT.  The suggested expert system's results indicate that it is suitable for use in for the security. In the fog model, the blockchain technology approach also helps to address latency, centralization, and scalability difficulties.

Published
2022-09-16
How to Cite
Parveen, K., Daud, M., & Yamin Siddiqu, S. (2022). Smart Detection of Cardiovascular Disease Using Gradient Descent Optimization. Lahore Garrison University Research Journal of Computer Science and Information Technology, 6(03), 35-42. https://doi.org/10.54692/lgurjcsit.2022.0603334
Section
Articles