Design for a Digital Twin in Clinical Patient Care
Journal:
arXiv
Published Date:
May 2, 2025
Abstract
Digital Twins hold great potential to personalize clinical patient care,
provided the concept is translated to meet specific requirements dictated by
established clinical workflows. We present a generalizable Digital Twin design
combining knowledge graphs and ensemble learning to reflect the entire
patient's clinical journey and assist clinicians in their decision-making. Such
Digital Twins can be predictive, modular, evolving, informed, interpretable and
explainable with applications ranging from oncology to epidemiology.
