Rafe Mcbeth
Rafe McBeth, PhD
Assistant Professor of Clinical Radiation Oncology
Department: Radiation Oncology
Contact information
3400 Civic Center Boulevard
Philadelphia, PA 19104
Philadelphia, PA 19104
Publications
Education:
BS (Physics)
Colorado State University, 2010.
BS (Minor: Mathematics, Biomedical Engineering)
Colorado State University, 2010.
MS (Radiation Physics)
Colorado State University, 2012.
PhD (Radiation Physics)
Colorado State University, 2017.
Permanent linkBS (Physics)
Colorado State University, 2010.
BS (Minor: Mathematics, Biomedical Engineering)
Colorado State University, 2010.
MS (Radiation Physics)
Colorado State University, 2012.
PhD (Radiation Physics)
Colorado State University, 2017.
Description of Clinical Expertise
Implementation of artificial intelligence in clinical radiation oncologyDescription of Research Expertise
Computational methods in radiation oncology including artificial intelligence, Monte Carlo simulation, and automation.Selected Publications
Hai Siong Tan, Kwancheng Wang, Rafe Mcbeth: Uncertainty-Error correlations in Evidential Deep Learning models for biomedical segmentation. International Conference on Technologies and Applications of Artificial Intelligence Dec 2025.Satvik Tripathi, Dana Alkhulaifat, Florence X Doo, Pranav Rajpurkar, Rafe McBeth, Dania Daye, Tessa S Cook: Development, Evaluation, and Assessment of Large Language Models (DEAL) Checklist: A Technical Report. NEJM AI May 2025.
Riqiang Gao, Mamadou Diallo, Han Liu, Anthony Magliari, Jonathan Sackett, Wilko Verbakel, Sandra Meyers, Rafe Mcbeth, Masoud Zarepisheh, Simon Arberet, Martin Kraus, Florin C Ghesu, Ali Kamen: Automating High Quality RT Planning at Scale. arXiv Jan 2025.
Hai Siong Tan, Kuancheng Wang, Rafe McBeth: Evidential Physics-Informed Neural Networks. arxiv Jan 2025.
D. Wang S.H. Lee N. Yegya-Raman S.J. Feigenberg G.D. Kao A.L. Largent C. Friedes M. Iocolano R. McBeth L. Duan B. Li Y. Fan Y. Xiao: Interpretable Machine Learning Models for Severe Esophagitis Prediction in LA-NSCLC Patients Treated with Chemoradiation Therapy. ASTRO Annual meeting 2023 October 2024.
Daniel A. Alexander, Rafe McBeth : Enhancing Safety in Clinical AI Auto-Segmentation: Utilizing an Open-Source Model for Quality Assurance and Error Reduction. AAPM Annual meeting 2024 July 2024.
Brook Byrd, Daniel Alexander, William Ross Green, Steven Philbrook, Rafe McBeth: Utilizing a Vision-Language Pre-Training (VLP) Model for Rapid APBI Breast Target Auto-Segmentation. AAPM Annual Meeting 2024 July 2024.
Daniel Alexander, Steven Philbrook, William Ross Green, Rafe McBeth: Evaluation of a Commercial Autosegmentation System for HN Oars: A Large US Institutional Experience. AAPM Annual Meeting July 2024.
Julia Pakela, Rafe McBeth, Daniel Alexander, Wei Zou, Alireza Kassaee: Lung Tumor Motion Characterization for Proton Therapy Decision Support. AAPM Annual Meeting July 2024.
Joseph Shields, Steven Philbrook, Rafe McBeth: Developing an Esapi-Based Autoplanning Method for Volume-Modulated Arc Therapy for Accelerated Partial Breast Irradiation on the Halcyon. AAPM Annual Meeting 2024 July 2024.