Machine Learning for Multiscale Analysis of Biomedical Data

Artificial intelligence to find the shapes of data in COVID-19

The key objective of this project is to use computational power to simulate machine learning algorithms that incorporate different scales that represent the interactions of COVID-19 and the immune system, whereby this simulator would help to dissect between mild and severe COVID-19 patients. Consequently, this information will be introduced at the epidemiological level to obtain complex algorithms for studying different therapeutic strategies during a pandemic. Finally, algebraic topology can provide us with new insights to understand how the complex organizational features of our social mixing patterns might impact on the transmission of infections.

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Period: 2021 - 2022