Extending artificial intelligence in the operating room

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. However, those detections should be interpretable, or more actionable in order to be audited or reviewed. This project applies various ‘explainable AI’ (XAI) technologies, which will allow us to evaluate the impact of solutions, which generalizes across the healthcare syste

Faculty Supervisor:

Sanja Fidler;Graeme Hirst;Marzyeh Ghassemi;Jimmy Ba

Student:

Partner:

Surgical Safety Technologies Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program: