Digital Twinning Application in Healthcare - Transforming Healthcare, Episode...
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Key Takeaways
- Digital twins create patient-specific 3D models from genetic, physiological, and lifestyle data to simulate individual organ function and pathology.
- Cardiac digital twins can model arrhythmias (e.g., potassium overload) and post-surgical recovery to predict and prevent adverse events.
- Personalized medicine uses digital twins to simulate thousands of treatment options before selecting the optimal drug for the actual patient.
- Swedish consortium strategy: build network models of molecular/environmental factors, test drugs on digital twins, then treat real patients.
- AI-driven digital twin technology enables clinicians to visualize circulation, electrical signals, and treatment outcomes before intervention.
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Hi, this is Anthon Bash from Cincinnati Children's Hospital. Previous video, we introduced the concept of digital twinning. We got a couple questions about how to apply digital twinning in healthcare. Here we are explaining digital twinning concept with a few examples. Digital twin technology can be used to generate a virtual healthcare facility or human body. We can create an individual's genetic makeup, physiological characteristics, and lifestyle habits. AI helps in the design of digital twins to put together organs physiological data to output a 3D image. Then this 3D image can be modeled to specific patients from their specific parameters. This is a digital twin of a human heart and you can see the circulation. In this one, we see a digital twin of a human heart in case of potassium overload, which induces arrhythmias. It is critical to understand, predict, and avoid cardiac arrests. And this one here is a digital twin of a heart restarting after surgery. First, you can see the imbalances of electrical signals going through the heart before an actual heartbeat. Here is another example of using digital twins in healthcare, personalized medicine. With this digital twin of the patient's heart and the data from similar cases, can predict the best possible outcome for the patient. And the next step is simulating various options for a certain procedure, which enables doctors to select the one with the optimal computer result. In this paper, they mentioned the Swedish digital twin consortium aims to develop a strategy for personalized medicine. And this strategy is based on constructing unlimited copies of network models of all molecular, phenotypical, and environmental factors, and treating those digital twins with thousands of drugs in order to identify the best performing drug. And the last step is treating the actual patient with this drug. Download the stay current app, follow us on social media and subscribe on YouTube channel. And remember, knowledge should be free.