Human Digital Twins and Machine Learning Applications in Precision Medicine and Surgery: Current State and Future Directions

Author:

Basu Arindam

Abstract

Human digital twins (“HDT”) are one-on-one digital replicas of human beings, organs such as the heart and lungs, or pathophysiological processes such as immune systems, where the digital replicas and the physical counterparts are tethered with each other. Critical to the HDT is a connector (“bridge”) that links the human and digital counterparts. Sensors on human bodies obtain real-time pathophysiological data and pass them through the bridge to the digital twin. The digital twin runs artificial intelligence/machine learning (“AI/ML”) algorithms on this input and the resulting output is passed via the bridge to the connected human being. This combination of a connected human being, a digital counterpart and the bridge is unique to HDTs distinguishing them from simulations, clones, and digital assistants. HDTs are the prime drivers of precision medicine and personalised care. While the most common clinical uses of HDTs are as yet in cardiology and surgery, as this technology will evolve, new uses of HDT will be explored and will bring about a paradigm shift in medical care. In this chapter we have discussed the technology of HDTs, principles, methods of construction, and use of HDTs. We also discuss key limitations and human ethics related to the HDTs.

Publisher

IntechOpen

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