activity
20172019
collaborators

6 papers

physics.med-ph2019

The importance of evaluating the complete automated knowledge-based planning pipeline

Aaron Babier, Rafid Mahmood, Andrea L. McNiven +2

We determine how prediction methods combine with optimization methods in two-stage knowledge-based planning (KBP) pipelines to produce radiation therapy treatment plans. We trained…

math.OC2019

Response time optimization for drone-delivered automated external defibrillators

Justin J. Boutilier, Timothy C. Y. Chan

Out-of-hospital cardiac arrest (OHCA) claims over 400,000 lives each year in North America and is one of the most time-sensitive medical emergencies. Drone-delivered automated exte…

stat.AP2019

An Inverse Optimization Approach to Measuring Clinical Pathway Concordance

Timothy C. Y. Chan, Maria Eberg, Katharina Forster +4

Clinical pathways outline standardized processes in the delivery of care for a specific disease. Patient journeys through the healthcare system, though, can deviate substantially f…

physics.med-ph2018

Knowledge-based automated planning with three-dimensional generative adversarial networks

Aaron Babier, Rafid Mahmood, Andrea L. McNiven +2

We develop a knowledge-based automated planning (KBAP) pipeline that generates treatment plans using deep neural network architectures for predicting 3D doses. Our pipeline consist…

math.OC2018

Inverse optimization for the recovery of constraint parameters

Timothy C. Y. Chan, Neal Kaw

Most inverse optimization models impute unspecified parameters of an objective function to make an observed solution optimal for a given optimization problem with a fixed feasible…

math.OC2017

Trade-off preservation in inverse multi-objective convex optimization

Timothy C. Y. Chan, Taewoo Lee

We present a new inverse optimization methodology for multi-objective convex optimization that accommodates an input solution that may not be Pareto optimal and determines a weight…