Digital Twin is a dynamic digital illustration of the patient’s physiology and anatomy using various computational models. These models are computational fluid dynamics and finite element analysis that are used to being periodically updated from various sources. These sources are clinical and laboratory findings, wearable devices, and biomedical-enabled sensors. Potential information gained from these sources is utilized to generate a digital twin of patients or organs which provides the biochemical, physiological, anatomical, and functional behavior of the actual system. Integration of `machine and deep learning models’ and `virtual and augmented reality models’ with digital twin can help doctors for customization of therapeutic paths and for reducing the need for invasive intervention procedures. Additionally, digital twin-based models are helpful for researchers to examine various diseases, drug interactions and medical equipment.

Recently, many digital twin-based healthcare systems have been designed and implemented that have shown remarkable performance. However, it is still an open area of research. There is space to explore the implementation of digital twins for drug discovery, drug-drug interactions, automated patients’ diagnosis and treatment. Additionally, secure manufacturing of digital twins is required that guarantees trust, authenticity, quality, safety, traceability, and compliance.

The main objective of this Special Issue is to document the current state-of-the-art, compare and contrast perspectives, and recognize future directions of digital twin applications in the healthcare industry. We welcome original research and review articles.

Potential topics include but are not limited to the following:

• Digital Twins blueprint
• Digital Twins standardization
• Digital Twins role in the digital transformation process
• Overlapping of physical and digital twins
• Personal Digital Twins
• Societal and ethical aspects
• Cognitive Digital Twins
• Digital Twins theory and modelling
• Digital Twins experience from concrete applications
• Prognostics and health monitoring
• Healthcare 4.0
• Internet of Things
• Cyber-physical systems
• Cybersecurity