85 citations · 164 across the 5 of their papers we have counts for
5 papers
A comparison of Monte Carlo dropout and bootstrap aggregation on the performance and uncertainty estimation in radiation therapy dose prediction with deep learning neural networks
Dan Nguyen, Azar Sadeghnejad Barkousaraie, Gyanendra Bohara +4
Recently, artificial intelligence technologies and algorithms have become a major focus for advancements in treatment planning for radiation therapy. As these are starting to becom…
Using Deep Learning to Predict Beam-Tunable Pareto Optimal Dose Distribution for Intensity Modulated Radiation Therapy
Gyanendra Bohara, Azar Sadeghnejad Barkousaraie, Steve Jiang +1
We propose to develop deep learning models that can predict Pareto optimal dose distributions by using any given set of beam angles, along with patient anatomy, as input to train t…
A reinforcement learning application of guided Monte Carlo Tree Search algorithm for beam orientation selection in radiation therapy
Azar Sadeghnejad-Barkousaraie, Gyanendra Bohara, Steve Jiang +1
Due to the large combinatorial problem, current beam orientation optimization algorithms for radiotherapy, such as column generation (CG), are typically heuristic or greedy in natu…
Incorporating human and learned domain knowledge into training deep neural networks: A differentiable dose volume histogram and adversarial inspired framework for generating Pareto optimal dose distributions in radiation therapy
Dan Nguyen, Rafe McBeth, Azar Sadeghnejad Barkousaraie +4
We propose a novel domain specific loss, which is a differentiable loss function based on the dose volume histogram, and combine it with an adversarial loss for the training of dee…
Crucial events, randomness and multi-fractality in heartbeats
Gyanendra Bohara, David Lambert, Bruce J. West +1
We study the connection between multi-fractality and crucial events. Multi-fractality is frequently used as a measure of physiological variability. Crucial events are known to play…