Vivli Data Challenge 2025 - Nachtrab

For the purpose of participating in the Vivli AMR 2025 challenge in the context of a student internship at imperial college with prof Leonid Chindelevitch, we aim to research the phenotype/genotype link with a view on potentially shortening identification times by bypassing the sequencing step, improving patient outcomes, and as a result reduce the usage of broad spectrum treatments administered in cases of sepsis, helping prevent the creation and spread of resistant strains.

The data will also be used to explore various machine learning models and techniques, and their applications to predicting resistance profiles and strain evolution based on both pheno- and geno- typic data, with the aim of being able to improve understanding of the process of resistance acquisition, both its rate as well as its most important factors, with the goal of better informing prevention techniques and predicting potential future resistances.