Rafe Mcbeth

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Rafe McBeth, PhD

Assistant Professor of Clinical Radiation Oncology
Department: Radiation Oncology

Contact information
3400 Civic Center Boulevard
Philadelphia, PA 19104
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.
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Description of Clinical Expertise

Implementation of artificial intelligence in clinical radiation oncology

Description of Research Expertise

Computational methods in radiation oncology including artificial intelligence, Monte Carlo simulation, and automation.

Selected Publications

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.

Hai Siong Tan, Kuancheng Wang, Rafe Mcbeth: Exploring UMAP in hybrid models of entropy-based and representativeness sampling for active learning in biomedical segmentation. Computers in Biology and Medicine 176, June 2024.

Jace Grandinetti, Rafe McBeth: From Generalist to Specialist: Improving Large Language Models for Medical Physics Using ARCoT. arXiv May 2024.

Hai Siong Tan, Kuancheng Wang, Rafe Mcbeth: Deep Evidential Learning for Dose Prediction. arXiv April 2024.

Kuancheng Wang, Hai Siong Tan, Rafe Mcbeth: Swin UNETR++: Advancing Transformer-Based Dense Dose Prediction Towards Fully Automated Radiation Oncology Treatments. Extended Abstract presented at Machine Learning for Health (ML4H) symposium 2023, arXiv Nov 2023.

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Last updated: 08/16/2024
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