Chapter 8 Digital twins in medicine: leveraging machine learning for real-time diagnosis and treatment

Abstract

The revolutionary field of digital twins in medical practice, which uses artificial intelligence (AI) to create accurate digital dupes of actual human bodies and improve medical diagnosis and therapy, will be a key area of focus for this study. As a way to illustrate the processes needed to generate an exact copy employing machine learning computational methods. The development of a digital twin in the health industry is the target of this review. These digital twins allow for swift diagnosis as well as tailored approaches to therapy and significantly improve the quality of life. The research conducted indicates when applied on the Internet of medical things, conventional machine learning techniques are efficient, quick, and economical. Additionally, it focuses on the positive aspects of embracing AI-driven digital twins for healthcare purposes like the enhancement of diagnostic precision and the capacity for efficient organization. Additionally, by automating procedures, decreasing medical errors, and giving physicians access to real-time data that can aid in selection, digital twins can assist to save costs while also boosting efficiency. Furthermore to contemplate on the applications in real life, the study additionally investigates the future potential avenues as well as the part advancing technology and AI techniques throughout the advancement of this revolutionary technology in the near future. This is designed to provide insights and a pathway for researchers, medical experts, and technology enthusiasts who are interested in leveraging future health practices due to the use of digital twins to enhance patient car

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