Assessment of Digital Twins in Healthcare and Future Industry 6.0

The combination of digital twin technologies and AI could transform healthcare. A "digital twin" is a computer model of a physical object, process, or system. Digital twins can represent physical objects as well as span the real and virtual worlds. Industry 4.0 need this technology for numerous needs. This paper outlines key findings from a comprehensive literature review on digital twins in healthcare innovation, focusing on healthcare system optimization, medical research, tailored patient care, and medical device development. Digital twins generate virtual patients, medical gadgets, and healthcare facilities for personalized treatment, predictive analytics, and real-time monitoring. AI algorithms that improve digital twin prediction give healthcare practitioners evidence-based guidance and decision support tools. When paired with IoT and machine learning, digital twins can improve healthcare delivery through proactive interventions, remote patient monitoring, and virtual healthcare services. Data protection, interoperability, scalability, and regulatory compliance remain major challenges. Despite these obstacles, digital twin technology could improve patient outcomes, operations, and new ideas in healthcare. Digital twins can save money, discover inefficiencies, and develop a material consumption tool monitoring system. For any production process improvement, manufacturers produce digital copies of unique machinery, systems, or processes. Industry 4.0 and future R&D should address these issues to realize digital twins' healthcare revolution promise.