b9
13
d
d
69
f
15
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1
24
19
38
11
17
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15
15
11
3a
9
13
d
9
9
19
9
d
11
9
9
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13
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19
49
19
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18
1 18
1 1 1 2b
11
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25
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26 Rafe McBeth, PhD
1 19 19 31 19 65 19 19 49 31 31 19 19 19 19 19 45
3b
19
19
19
1
1
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2d
79
2f
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1
5
2f
4c
7
Assistant Professor of Clinical Radiation Oncology
1874 Department: Radiation Oncology
11 131 18
e
1
5
25
5
e
Contact Information
c
92
3400 Civic Center Boulevard
Philadelphia, PA 19104
49
1e
9
e
Publications
70 b
17
9
12
Links
d-
103
- Search PubMed for articles
- Google Scholar 62
1b
b
Education
d-
1d
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2e
BS (Physics)
55
Colorado State University, 2010
1d
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51
BS (Minor: Mathematics, Biomedical Engineering)
55
Colorado State University, 2010
1d
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38
MS (Radiation Physics)
55
Colorado State University, 2012
1d
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39
PhD (Radiation Physics)
55
Colorado State University, 2017
1a
1 1 1 2b
Description of Research Expertise
7fComputational methods in radiation oncology including artificial intelligence, Monte Carlo simulation, and automation.
1 2bDescription of Clinical Expertise
50Implementation of artificial intelligence in clinical radiation oncology
1 1 1 1fSelected Publications
5-
5
- 9f Hai Siong Tan, Kwancheng Wang, Rafe Mcbeth : Uncertainty-Error correlations in Evidential Deep Learning models for biomedical segmentation 73 International Conference on Technologies and Applications of Artificial Intelligence Dec 2025 5
- e7 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 26 NEJM AI May 2025 5
- 103 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 24 arXiv Jan 2025 5
- 6d Hai Siong Tan, Kuancheng Wang, Rafe McBeth : Evidential Physics-Informed Neural Networks 24 arxiv Jan 2025 5
- 10 D. Wang a S.H. Lee 10 N. Yegya-Raman 11 S.J. Feigenberg a G.D. Kao e A.L. Largent c C. Friedes d M. Iocolano b R. McBeth 9 L. Duan 7 B. Li 8 Y. Fan 98 Y. Xiao : Interpretable Machine Learning Models for Severe Esophagitis Prediction in LA-NSCLC Patients Treated with Chemoradiation Therapy 3c ASTRO Annual meeting 2023 October 2024 5
- b3 Daniel A. Alexander, Rafe McBeth : Enhancing Safety in Clinical AI Auto-Segmentation: Utilizing an Open-Source Model for Quality Assurance and Error Reduction 38 AAPM Annual meeting 2024 July 2024 5
- ca 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 38 AAPM Annual Meeting 2024 July 2024 5
- be Daniel Alexander, Steven Philbrook, William Ross Green, Rafe McBeth : Evaluation of a Commercial Autosegmentation System for HN Oars: A Large US Institutional Experience 33 AAPM Annual Meeting July 2024 5
- a3 Julia Pakela, Rafe McBeth, Daniel Alexander, Wei Zou, Alireza Kassaee : Lung Tumor Motion Characterization for Proton Therapy Decision Support 33 AAPM Annual Meeting July 2024 5
- cd 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 38 AAPM Annual Meeting 2024 July 2024 6