Digital twins for cardiovascular diseases: towards personalised and sustainable care

Abstract

Cardiovascular diseases (CVD) remain a significant global health challenge, necessitating innovative approaches. The emergence of digital twin technology, which creates virtual replicas of real-world objects or systems, has shown great promise in various fields, including healthcare. In the context of CVD, digital twins offer a unique opportunity for personalised medicine and risk assessment by integrating diverse data sources and generating patient-specific computational models. This viewpoint explores the potential applications and benefits of digital twins in CVD management, including personalised risk assessment, disease modelling, treatment optimisation, and remote patient monitoring. Additionally, it discusses the challenges and limitations associated with implementing digital twins in the context of cardiovascular diseases. Digital twins have the potential to revolutionise CVD management by providing a dynamic and individualised approach to risk assessment, treatment optimisation, and proactive care. Collaborative efforts between healthcare professionals, researchers, and technology developers are necessary to overcome these challenges and fully realise the potential of digital twins in improving patient outcomes and revolutionising cardiovascular healthcare. Future directions include advancements in artificial intelligence, integration of omics data, real-time monitoring, virtual clinical trials, patient empowerment, and integration with healthcare systems. Digital twins can foster a more personalised approach to managing CVD.

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