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; Gyanendra Bohara; Chenyang Shen; Xun Jia; Steve B. Jiang (CoRR, 2019)

Using Monte Carlo dropout and bootstrap aggregation for uncertainty estimation in radiation therapy dose prediction with deep learning neural networks. - Dan Nguyen; Azar Sadeghnejad-Barkousaraie; Gyanendra Bohara; Anjali Balagopal; Rafe McBeth; Mu-Han Lin; Steve B. Jiang (CoRR, 2020)

Site-Agnostic 3D Dose Distribution Prediction with Deep Learning Neural Networks. - Maryam Mashayekhi; Itzel Ramirez Tapia; Anjali Balagopal; Xinran Zhong; Azar Sadeghnejad-Barkousaraie; Rafe McBeth; Mu-Han Lin; Steve B. Jiang; Dan Nguyen (CoRR, 2021)

A Proof-of-Concept Study of Artificial Intelligence Assisted Contour Revision. - Ti Bai; Anjali Balagopal; Michael Dohopolski; Howard E. Morgan; Rafe McBeth; Jun Tan; Mu-Han Lin; David J. Sher; Dan Nguyen; Steve B. Jiang (CoRR, 2021)

Prediction of Type and Recurrence of Atrial Fibrillation after Catheter Ablation via Left Atrial Electroanatomical Voltage Mapping Registration and Multilayer Perceptron Classification: A Retrospective Study. - Qiyuan An; Rafe McBeth; Houliang Zhou; Bryan Lawlor; Dan Nguyen; Steve B. Jiang; Mark S. Link; Yingying Zhu 004 (Sensors, 2022)

Swin UNETR++: Advancing Transformer-Based Dense Dose Prediction Towards Fully Automated Radiation Oncology Treatments. - Kuancheng Wang; Hai Siong Tan; Rafe McBeth (CoRR, 2023)

Exploring UMAP in hybrid models of entropy-based and representativeness sampling for active learning in biomedical segmentation. - Hai Siong Tan; Kuancheng Wang; Rafe McBeth (Comput. Biol. Medicine, 2024)

Deep evidential learning for radiotherapy dose prediction. - Hai Siong Tan; Kuancheng Wang; Rafe McBeth (Comput. Biol. Medicine, 2024)

Deep Evidential Learning for Dose Prediction. - Hai Siong Tan; Kuancheng Wang; Rafe McBeth (CoRR, 2024)

From Generalist to Specialist: Improving Large Language Models for Medical Physics Using ARCoT. - Jace Grandinetti; Rafe McBeth (CoRR, 2024)

Uncertainty-Error correlations in Evidential Deep Learning models for biomedical segmentation. - Hai Siong Tan; Kuancheng Wang; Rafe McBeth (CoRR, 2024)

Automating High Quality RT Planning at Scale. - Riqiang Gao; Mamadou Diallo; Han Liu; Anthony Magliari; Jonathan Sackett; Wilko Verbakel; Sandra Meyers; Masoud Zarepisheh; Rafe McBeth; Simon Arberet; Martin Kraus; Florin C. Ghesu; et al. (CoRR, 2025)

Evidential Physics-Informed Neural Networks. - Hai Siong Tan; Kuancheng Wang; Rafe McBeth (CoRR, 2025)