AI for Laparoscopic Cholecystectomy decision support

My project’s goal is to improve the model, which predicts in real-time zones, where it is safe to dissect during laparoscopic surgery. I am going to work on the ways to mitigate tool bias of the current model, as it presence could result into misleading of the surgeon, who performs an operation and, as a result, cause significant injuries. Eventually, this project will greatly benefit all future research around tool bias problem during surgeries, deepen human knowledge about different biases in AI models and prolong the lives of patients.

Faculty Supervisor:

Michael Brudno

Student:

Partner:

Taras Shevchenko National University of Kyiv

Discipline:

Computer science

Sector:

Artificial Intelligence; Technology

University:

University of Toronto

Program:

Globalink Research Award

Current openings

Find the perfect opportunity to put your academic skills and knowledge into practice!

Government

International

Load More

International

Load More