Sharma, Vikas; Sharma, Kapil and Kumar, Akshi. 2024. 'AI and Digital Twins Transforming Healthcare IoT'. In: 14th International Conference on Cloud Computing, Data Science & Engineering. Noida, India 18 - 19 January 2024. [Conference or Workshop Item]

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Abstract or Description

In this age of digital and smart healthcare, cutting-edge technologies are being used to improve operations, patient well-being, life expectancy, and healthcare costs. Digital Twins (DT) have the potential to significantly change these new technologies. DTs could revolutionise digital healthcare delivery with extraordinary creativity. A digital representation of a physical asset that is always its digital twin due to real-time data processing. This paper proposes and builds a DT-based intelligent healthcare system that is aware of its environment. This approach is a great advance for digital healthcare and could improve service delivery. Our most notable contribution is a machine learning-based electrocardiogram (ECG) classifier model for cardiac diagnostics and early problem detection. Our cardiac models predict some situations with exceptional accuracy when applied to different ways. These findings highlight the potential for Digital Twins in healthcare to create intelligent, comprehensive, and scalable Health-Systems that improve patient-physician communication. Our ECG classifier also sets a precedent for using Artificial Intelligence (AI) and Machine Learning (ML) to continually monitor wide range of human body data and identify outliers. ECG data processing has improved significantly using neural network-based algorithms over classic machine learning methods. In conclusion, our work integrates digital twins with cutting-edge AI and machine learning to revolutionise healthcare. Future healthcare will be predictive and improve lives.

Item Type:	Conference or Workshop Item (Paper)
Identification Number (DOI):	https://doi.org/10.1109/Confluence60223.2024.10463366
Additional Information:	“© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”
Keywords:	Digital Twin, Healthcare, Internet of Things (IoT), Artificial Intelligence (AI)
Departments, Centres and Research Units:	Computing
Dates:	Date Event 12 December 2023 Accepted 21 March 2024 Published
Event Location:	Noida, India
Date range:	18 - 19 January 2024
Item ID:	37513
Date Deposited:	05 Sep 2024 13:45
Last Modified:	05 Sep 2024 16:14
URI:	https://research.gold.ac.uk/id/eprint/37513

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