Machine learning and the COVID Black Box: Safe monitoring of COVID-19 ICU beds, assessment centres, and surgeries

The project aims to optimize healthcare provider and patient safety and monitor PPE use, to optimize resource utilization during the COVID-19 pandemic. Assessment of surgical data from an operating room is a complex process that may require significant resources such as expert input and advanced technology. Automation brings a considerable opportunity to greatly reducing these significant resource requirements – e.g., using computer vision software to detect clinically relevant actions during surgery. With the data collected from operating room black box, the main aim is to analyze 1) hand hygiene, 2) adherence to personal protective equipment (PPE) protocols, 3) breaches in safety, and 4) system vulnerability in Ontario.

Faculty Supervisor:

Animesh Garg

Student:

Priya Thakur

Partner:

Surgical Safety Technologies Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto