Blockchain-based digital twin to predict heart attacks

Venkatesh Upadrista, Sajid Nazir, Huaglory Tianfield

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

1 Citation (Scopus)

Abstract

The digital twin of a person is a virtual representation of that individual and is a model that can be created with real-time data, such as age, weight, past medical history, and current real-time health readings. This research work describes the creation of a digital twin that can be used to predict heart attacks, thereby enabling doctors to perform proactive medical interventions to save human lives. We have developed an application using a headless architecture to enable seamless integration with other medical devices for other critical health conditions. We have used blockchain for security and machine learning to predict heart attacks. The results of our implementation show that heart attack can be predicted with 97.1% accuracy, and in parallel, doctors can be immediately notified of an imminent heart attack risk in real time using an email. We have also shown that our implementation is tamper-proof and highly reliable by testing the application using the concept of chaos engineering.

Original languageEnglish
Title of host publicationBlockchain for Healthcare 4.0: Technology, Challenges, and Applications
EditorsRishabh Malviya, Sonali Sundram
Place of PublicationBoca Raton
PublisherCRC Press
Chapter16
Number of pages16
Edition1st
ISBN (Electronic)9781003408246
ISBN (Print)9781032524863
DOIs
Publication statusPublished - 17 Dec 2023

ASJC Scopus subject areas

  • General Computer Science

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