Table of Content

Applications of Digital Twins in Intelligent Healthcare Systems

Submission Deadline: 25 March 2023 Submit to Special Issue

Guest Editors

Prof. Muhammad Asghar, Universiti Kuala Lumpur, Malaysia; Gomal University, Pakistan.
Prof. Shakeel Ahmad, King Abdul Aziz University (KAU), Saudi Arabia.
Dr. Fazal Masud Kundi, Gomal University, Pakistan.

Summary

The digital information permeates most Complex Systems in the present Big Data era. This is especially true as a result of IoT's pervasive adoption across several industries. As a result of this merger, businesses will be able to improve their operations and become more competitive. The advent of cheaper Digital Twins has great potential for advancing such prospects and influencing the development of integrated applications.


Digital twins are regarded as a new starting point for today's intelligent healthcare system. A digital twin is a computerised duplicate of a real-world object. You can get a clearer picture of your equipment's status and utilise it or fix it more wisely. DTs can use AI, ML, Cognitive Computing, Edge and Cloud Computing, Augmented and Virtual Reality to predict the future of complex systems instead of evaluating the past. enabling ex-ante intelligent healthcare practices. Digital twins help patient care and research in healthcare. By recreating a patient's brain, scientists may study disorders and discover how treatments operate on human cells. Hospitals can also cut down on expenses related to personnel and research when digital twins are used in place of real patients. To get these benefits, we need to solve the following problems: how to accurately represent physical objects; how to let them change on their own in real time; how to connect processes during runtime; how to find and solve conflicts; how to handle human interaction; and how to keep things safe and secure. To do this, we must provide conceptualizations of DTs, define new DT engineering methods, create user-friendly software for developing DT solutions, and encourage the use of DT in intelligent healthcare systems.

This Special Issue's goal is to compile observational, innovative, empirical, and conceptual investigation monitoring original and unpublished findings that have an impact on the description, layout, integration, and utilisation of DT, focus attention on the ongoing improvement of healthcare systems incorporating DTs, and recommendation software applications, actual experiences, utilisation, and research reports.


Keywords

Possible topics could include, but are not limited to:
• Conceptualization of the Digital Twin in Healthcare
• Safety and Security in Healthcare's Adoption of Digital Twins
• The Creation of Digital Twin Healthcare Platforms
• Collaboration between Digital Twins for intelligent healthcare
• Healthcare data analytics and visualisation in real time
• Domain-specific datasets for digital twins in healthcare
• Diagnosis and treatment of diseases through digital twin engineering
• Collaboration and communication between healthcare individuals and digital twins
• Applying Cognitive Computing to Healthcare Digital Twins
• Healthcare digital twins using edge, fog, and cloud computing
• Digital Twins in Public Healthcare: Case Studies and Practical Validation
• Digital Twins for healthcare that use Augmented and Virtual Reality

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