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Next-generation physician and staff scheduling system designed to reduce the burden of manual scheduling

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schedulEQ enhances scheduling workflow for administrators using machine learning automation. Physicians and staff are provided greater autonomy and work-life balance through balanced and flexible scheduling options.


Enable greater work-life balance by increasing scheduling flexibility. Workload forecasting unlocks the potential for individuals to modify their own schedules while ensuring adequate clinical coverage and appropriate workload distribution.

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Reduce the manual burden of scheduling by leveraging machine learning to facilitate schedule creation.


Predicting workload enables optimized scheduling to reduce overstaffing and understaffing.

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Staff scheduling is a manually intensive and time-consuming process requiring the scheduler to juggle multiple priorities, including clinical expertise, work productivity, away requests, location, and fairness. schedulEQ uses machine learning to help automate this process to reduce the manual burden of scheduling.

Heidi Schmidt, MD.

Department Head Medical Imaging and Program Medical Director, Joint Department of Medical Imaging. University Health Network
Toronto, Canada

schedulEQ has enabled us to efficiently manage and balance the clinical schedules of over 145 staff radiologists and fellows throughout our health system.”

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