Improvement of Radiation Therapy Through Staff Scheduling Optimization

The Challenge

The Princess Margaret Cancer Center is proposing an AI-based solution to optimize staff scheduling, increase efficiency, and improve staff satisfaction. The solution consists of several components: a workload predictor, an absence predictor, a monthly optimizer, a monthly re-optimizer, and a daily re-optimizer. These components leverage historical data, predict uncertainties, and utilize advanced algorithms to construct robust schedules, minimize operational costs, ensure sufficient coverage, and minimize disruptions to staff and patient schedules.



Scale AI investment


Total investment


“Implementing the AI-based solution is intended to positively impact Princess Margaret’s operations, staff satisfaction and patient care continuity. By reducing the time spent on scheduling tasks, team supervisors will hopefully be able to focus on mentoring, quality improvement projects, research, and enhancing the overall quality of care.”

— Philip Wong, Radiation Medicine Associate Director of ambulatory care, UHN Princess Margaret
Made possible through the
financial support of
Gouvernement du Québec
Gouvernement du Canada

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