Research output per year
Research output per year
Venkatesh Upadrista, Sajid Nazir, Huaglory Tianfield
Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review
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 language | English |
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Title of host publication | Blockchain for Healthcare 4.0: Technology, Challenges, and Applications |
Editors | Rishabh Malviya, Sonali Sundram |
Place of Publication | Boca Raton |
Publisher | CRC Press |
Chapter | 16 |
Number of pages | 16 |
Edition | 1st |
ISBN (Electronic) | 9781003408246 |
ISBN (Print) | 9781032524863 |
DOIs | |
Publication status | Published - 17 Dec 2023 |
Research output: Contribution to journal › Article › peer-review