Machine learning methods for automatic diagnosis, severity assessment, prognosis, and disease understanding of COPD

Chronic Obstructive Pulmonary Disease (COPD) is a progressive, debilitating, chronic respiratory disease that affects 600 million people worldwide and is responsible for 3 million deaths worldwide each year. Given the recent advances in artificial intelligence (AI) and the availability of large datasets from both the public and private sectors, our project applies AI to analyze large-scale medical datasets and develops tools capable of performing accurate diagnosis, severity assessment, and prognosis of COPD. Working in parallel, our project also aims to use AI to identify relevant biological markers that can predict current disease status and future progression. Ultimately, the tools developed and experimental results obtained throughout our research period will guide our partner organization in developing protocols for drug target discovery and validation, as well as therapy evaluation.

Faculty Supervisor:

Roger Tam

Student:

Lisa Tang

Partner:

Providence Health Care

Discipline:

Engineering - biomedical

Sector:

Medical devices

University:

Program:

Accelerate

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