AI Digital Twin In Healthcare: Use Case Studies and Best Practices

In this video, we explore how AI Digital Twins are transforming the healthcare industry by showcasing real-life use cases. Digital twins are virtual models that mimic real-world objects or processes, enabling healthcare providers to monitor and analyse data in real-time, predict outcomes, and optimise treatment plans.

We will highlight several case studies of digital twins in healthcare, including patient monitoring, drug development, and disease management. We'll also discuss the benefits of digital twins, such as improved accuracy, efficiency, and cost-effectiveness, and how they can be customised to meet the specific needs of patients and providers.

Whether you are a healthcare professional, researcher, patient, or interested in AIDT. This video provides valuable insights into how AI Digital Twins are revolutionising the way we approach healthcare. We invite you to join us on this exciting journey and learn more about the potential of this game-changing technology.

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Speaker - Yilin Li:
  / yilin-li-a3bb8b265  

Join the CeADAR community to learn more about digital twins and other DSAI topics: https://community.ceadar.ie/share/Pzy...

CeADAR links:
www.ceadar.ie
  / ceadarireland  
  / mycompany  

References:
1, Barbiero, P., Vinas Torne, R. and Lió, P., 2021. Graph representation forecasting of patient's medical conditions: Toward a digital twin. Frontiers in genetics, 12, p.652907.
2, Kovatchev, B., 2019. A century of diabetes technology: signals, models, and artificial pancreas control. Trends in Endocrinology & Metabolism, 30(7), pp.432-444.
3, Shang, J.K., Esmaily, M., Verma, A., Reinhartz, O., Figliola, R.S., Hsia, T.Y., Feinstein, J.A. and Marsden, A.L., 2019. Patient-specific multiscale modeling of the assisted bidirectional Glenn. The Annals of thoracic surgery, 107(4), pp.1232-1239.
4, Eddy, D.M. and Schlessinger, L., 2003. Archimedes: a trial-validated model of diabetes. Diabetes care, 26(11), pp.3093-3101.

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