Researchers from the University of Chicago and Weill Cornell Medicine have developed a digital twin of an infant biome via an AI tool named Q-net.
The AI can create a digital twin of the biome, enabling researchers to understand how microbiomes develop and interact with one another.
Due to the time-saving nature of digital twins, Q-net speeds up the process of studying these interactions, which would otherwise be time-consuming within a lab. The result is that Q-net can predict potential defects within infants with 76% accuracy that may harm development at increased rates.
The digital twin also enables scientists to narrow down potential treatment options for infants with possible use cases in virus evolution and other aspects of the body.
Overall, this development is an important milestone in the study of infant biomes, with Q-net being an effective tool in speeding up the detection and prevention of developmental issues within infants.
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