Syndrome Anomaly Detection System

Technologies that can speedily and efficiently analyze large amounts of data in real-time play a critical role in helping healthcare professionals and governments predict the impact and spread of a pandemic such as the Covid-19 virus over time. Our Syndrome Anomaly Detection System (SADS) is an innovative platform that uses artificial intelligence (AI) to capture a set of symptoms using conversations of patients with health practitioners. Machine learning (ML) algorithms are then used to classify and detect sudden increases in unusual syndromes in communities. SADS will immediately notify public health and government officials upon outbreak detection. SADS will allow governments to manage disease outbreaks efficiently and in real-time, save lives, reduce health care costs and hospitalizations.

Faculty Supervisor:

Jean-Paul Lam;Aaron Ward

Student:

Partner:

GoodLabs Studio Inc.

Discipline:

Physics

Sector:

Professional, scientific and technical services

University:

The University of Western Ontario

Program: