Development of artificial intelligence algorithms for microbiome-based classification of disease

The goal of this project is to help build artificial intelligence algorithms for the diagnosis of disease using data derived from the human microbiome. This project will be focused on implementing new statistical methods to reduce “noise” found in data from different sources, allowing for us to improve the training of artificial intelligence algorithms. Another focus of this project will be to implement new types of models that are better suited for microbiome data, allowing for more accurate predictions. With these improved models, Phyla (partner org) will be able to more accurately detect disease from the microbial profile of stool samples.

Faculty Supervisor:

Adam Oberman

Student:

Noah Marshall

Partner:

Phyla

Discipline:

Statistics / Actuarial sciences

Sector:

Health care and social assistance

University:

McGill University