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:

Graeme Hirst;Jimmy Ba;Sanja Fidler;Marzyeh Ghassemi

Student:

Mengxuan Lyu;Chantal Shaib;Jinyue Feng;Vaibhav Saxena

Partner:

Surgical Safety Technologies Inc

Discipline:

Computer science

Sector:

University:

Program:

Accelerate

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