Here's another video about digital twin technology… This time we're talking about applications of digital twin to healthcare.
Here's what you need to know about Digital Twins!
A digital twin is a virtual representation of an object or system that is updated from real-time data, and uses simulation, machine learning and reasoning to help decision-making. The first practical definition of digital twin originated from NASA in an attempt to improve physical model simulation of spacecraft in 2010.
With the help of a digital twin, companies can test and validate a product before it even exists in the real world. Generally, by creating a replica of the planned production process, a digital twin enables engineers to identify any process failures before the product goes into production.
The use of cognitive computing increases the abilities and scientific disciplines in the digital twin. Technologies and techniques such as Natural Language Processing (NLP), machine learning, object/visual recognition, acoustic analytics, and signal processing are just a few of features used for creating digital twins.
Going forward there will be a transition towards cheaper, more accessible, and easier to use digital twins culminating in its democratization. Individuals and smaller companies will have access to the benefits as well as larger companies, increasing the use of the technology rapidly.
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.
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