11 citations · 11 across the 3 of their papers we have counts for
5 papers
Optimizing Data Collection for Machine Learning
Rafid Mahmood, James Lucas, Jose M. Alvarez +2
Modern deep learning systems require huge data sets to achieve impressive performance, but there is little guidance on how much or what kind of data to collect. Over-collecting dat…
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…
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…
Automated Treatment Planning in Radiation Therapy using Generative Adversarial Networks
Rafid Mahmood, Aaron Babier, Andrea McNiven +2
Knowledge-based planning (KBP) is an automated approach to radiation therapy treatment planning that involves predicting desirable treatment plans before they are then corrected to…
An Ensemble Learning Framework for Model Fitting and Evaluation in Inverse Linear Optimization
Aaron Babier, Timothy C. Y. Chan, Taewoo Lee +2
We develop a generalized inverse optimization framework for fitting the cost vector of a single linear optimization problem given multiple observed decisions. This setting is motiv…