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.