Medical Operations Research Laboratory

The Medical Operations Research Lab (morLAB) has been a leader in developing OR and AI tools, from optimization to machine learning to simulation, to improve medical and healthcare decision-making since its founding in 2007. morLAB is based in the Department of Mechanical & Industrial Engineering at the University of Toronto and is directed by Professor Dionne M. Aleman.

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Research

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All Machine learning Optimization Networks Simulation

Prediction of COVID-19 severity

Predicting of COVID-19 hospitalization, ICU, and death at the time of RT-PCR testing, days in advance of a patient seeking medical care, allowing for improved care and resource allocation

Cancer treatment planning

Automating treatment protocol selection and the design and validation of radiation treatment plans to better treat cancer

Single-entry waitlist surgical scheduling

Scheduling surgeries in a central waitlist across multiple collaborating hospitals and surgeons to maximize total surgeries and minimize wait times

Transplant matching and survival prediction

Matching pools of kidney patients to eligible donors and predicting survival of bone marrow and liver transplants using machine learning

Pandemic modeling and planning

Predicting pandemic disease spread through very large agent-based simulations and optimizing mitigation strategies through graph theory and machine learning