Bio

I was born in Providence, RI and went to undergraduate at Rensselaer Polytechnic Institute in upstate NY for Mechanical and Nuclear Engineering. I worked for my first year out of undergraduate as process engineer in PA. From there I transitioned out of the private sector and commissioned as Surface Warfare Officer (Nuclear) in the U.S. Navy through OCS. I was on active duty for approximately 10 years including tours on the USS DECATUR and USS CARL VINSON. Both ships were based out of San Diego and all my deployments were in the Asia-Pacific region. My final tour was with Navy ROTC as Officer in Charge of NROTC Unit 73 in MA, during which I taught Leadership and Ethics and completed my M.S. in Engineering Management. I am currently studying Medicine here at Stanford University with an anticipated graduation date of 2027.

Honors & Awards

  • Research on thoracic SABR motion management highlighted., QuadShot (2025)
  • Navy and Marine Corps Commendation Medal, United States Navy (2023)
  • Navy and Marine Corps Achievement Medal (x2), United States Navy (2017, 2019)

Professional Affiliations and Activities

  • Member, Alpha Nu Sigma Nuclear Engineering Honors Society (2012 - Present)
  • Member, Pi Tau Sigma International Honor Society for Mechanical Engineering (2009 - Present)

Education & Certifications

  • Master of Science, Old Dominion University, Engineering Management (2023)
  • Bachelor of Science, Rensselaer Polytechnic Institute, Nuclear Engineering (2012)
  • Bachelor of Science, Rensselaer Polytechnic Institute, Mechanical Engineering (2012)

Contact

  • Academic
    campbm4@stanford.edu
    University - Student Department: School of Medicine Position: Graduate, Medicine

Links

Research Projects

  • Local Control by Motion Management Strategy of Thoracic Tumors: Secondary Analysis of the iSABR Trial (MedScholars Project)

All Publications

  • Local Control in Thoracic Stereotactic Ablative Radiotherapy: Analysis of Motion Management and Single Fraction Dosimetry from the iSABR trial. International journal of radiation oncology, biology, physics Jaoude, J. A., Cui, S., Fu, J., Worth, J. E., Campbell, M. J., Lau, B., Eswarappa, S., Richter, S. A., Meurice, N., Shirato, H., Taguchi, H., Gee, H., Romero, I. O., Dubrowski, P., Pham, D., Skinner, L., Butler, S. S., Kastelowitz, N., Chin, A. L., Gensheimer, M. F., Diehn, M., Loo, B. W., Moiseenko, V., Vitzthum, L. K. 2025

    Abstract

    Thoracic stereotactic ablative radiotherapy (SABR) is an effective treatment for lung tumors. We evaluated the association between tumor control and A) tumor respiratory motion and motion management approach and b) single fraction dose metrics in patients treated on a prospective clinical trial.We evaluated 235 patients with 277 thoracic tumors treated on the iSABR trial. Motion management approaches included motion inclusive (MI, 41%), MI with extreme breaths excluded (MI-EE, 13%), expiratory gating (Exp Gating, 24%), and inspiratory breath hold (IBH, 22%). Association between tumor motion, motion management technique and local recurrence (LR) was evaluated using Fine-Gray Analysis. Among the cohort of patients treated in a single fraction (150 tumors), we performed a tumor control probability (TCP) analysis for dose to the gross tumor (GTV) and planning treatment volumes (PTV).There was no significant difference in LR by tumor motion when dichotomized to < or ≥ 1 cm (3-year LR of 5.8% vs 6.3%, p = 0.98). Similarly, there was no difference in LR between patients treated with MI, MI-EE, Exp Gating, and IBH with 24-month estimates of 5.5%, 5.9%, 4.7% and 3.7%, respectively (p = 0.75). For tumors treated with single fraction SABR, GTV D68.3% and PTV D65.3% had the strongest correlation with local control (LC). TCP analysis demonstrated a statistically significant association with GTV D99.7%, D95%, and D68.3%. Rates of LC at 3-years were greater than 90% with a GTV D68.3% > 29.4 Gy and a GTV D95% > 28.1 Gy.These findings suggest motion management techniques including Exp Gating and IBH can adequately control for respiratory motion. Furthermore, single fraction SABR with 25 Gy resulted in high rates of LC for small tumors when using heterogenous dosimetry including 29.4 Gy to 68.3% of the GTV and 28.1 Gy to 95% of the GTV.

    View details for DOI 10.1016/j.ijrobp.2025.12.017

    View details for PubMedID 41418986

  • Bridging the Digital Divide: A Practical Roadmap for Deploying Medical Artificial Intelligence Technologies in Low-Resource Settings. Population health management Wong, E., Bermudez-Cañete, A., Campbell, M. J., Rhew, D. C. 2025

    Abstract

    In recent decades, the integration of artificial intelligence (AI) into health care has revolutionized diagnostics, treatment customization, and delivery. In low-resource settings, AI offers significant potential to address health care disparities exacerbated by shortages of medical professionals and other resources. However, implementing AI effectively and responsibly in these settings requires careful consideration of context-specific needs and barriers to equitable care. This article explores the practical deployment of AI in low-resource environments through a review of existing literature and interviews with experts, ranging from health care providers and administrators to AI tool developers and government consultants. The authors highlight 4 critical areas for effective AI deployment: infrastructure requirements, deployment and data management, education and training, and responsible AI practices. By addressing these aspects, the proposed framework aims to guide sustainable AI integration, minimizing risk, and enhancing health care access in underserved regions.

    View details for DOI 10.1089/pop.2024.0222

    View details for PubMedID 39899377