The Research will be supervised for Veos Digital by Dr. Mattia Giuseppe Bergomi to serve as Principal Investigator during 2021.
Objective
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia has spread rapidly across the world.
The disease did not spread homogeneously, leading scientists and MDs to investigate the correlation between the disease’s severity and the genetic repertoire of patients. Even among the same population, although most individuals show mild symptoms, a subset of highly symptomatic patients requires mechanical ventilation. The proportion of these severely infected patients varies across populations and—despite depending on the screening procedures adopted by each country—it hints at a population-based variability that could be explained at the genetic level.
Veos Digital’s research Lab works closely with the group of academics involved in this project to create advanced machine learning algorithms able to work on datasets composed of few but very high-dimensional samples (e.g., Whole Exome Sequencing, WES). These models will allow the group of geneticists and MDs that actively collected the data to determine which and how expressed genes interact nonlinearly, regulating (at least partially) the infection’s severity.
Given this aim, as a Lab, we focus on the explainability of the algorithms we are implementing, leveraging guarantees given by the mathematical frameworks we defined to describe our models.
For additional info, send an email to press (at) veos.digital