Research Summary

Maggie Chung, MD is an Assistant Professor in the Department of Radiology and Biomedical Imaging at the University of California, San Francisco, specializing in breast imaging. She earned her medical degree from the Warren Alpert Medical School of Brown University, completed her internship at Scripps Mercy Hospital in San Diego, and completed both her diagnostic radiology residency and breast imaging fellowship at UCSF. During residency, she received the Elmer Ng Outstanding Resident Award, the Margulis Society Resident Research Award, and the RSNA Roentgen Resident/Fellow Research Award.

Her research is supported by the National Institutes of Health, Breast Cancer Research Foundation, and Radiological Society of North America. Dr. Chung’s research focuses on the development and clinical translation of artificial intelligence tools for breast imaging. Her work spans simulated contrast-enhanced breast MRI using deep learning, breast cancer risk prediction models for personalized screening, and the use of risk models to support expedited mammogram assessment.

Dr. Chung is a member of the Science and Technology Resource Group within UCSF’s Center for Intelligent Imaging (ci²) and UCSF Clinical Trials Committee. She has served on the UCSF Radiology Residency Admissions Committee, the Quality Assurance Committee and as a UCSF representative to the California Radiological Society.

Research Funding

  • March 11, 2025 - February 28, 2030 - Pillar: Multi-Modal Imaging AI Models for Breast Cancer Risk , Co-Principal Investigator . Sponsor: NIH, Sponsor Award ID: R37CA289821
  • September 1, 2024 - August 1, 2027 - Mirai-MRI: Multi-site MRI Screening of AI Models for Breast Cancer Risk , Co-Principal Investigator . Sponsor: Breast Cancer Research Foundation, Sponsor Award ID: unknown
  • June 1, 2024 - May 1, 2026 - Deep-learning based simulated contrast breast MRI for supplemental breast cancer , Principal Investigator . Sponsor: Radiological Society of North America, Sponsor Award ID: unknown

Honors & Awards

  • Bakar Fellows Spark Award, UC Berkeley, 2024-2027
  • RSNA Research Scholar Award, Radiological Society of North America, 2024-2026
  • Jaws Award, Shark Tank, Society of Breast Imaging, 2024
  • Roentgen Resident/Fellow Research Award, Radiological Society of North America, 2022
  • Elmer Ng Outstanding Resident Award, UCSF, 2022
  • Margulis Society Resident Research Award, UCSF, 2022
  • Certificate of Merit, Educational Exhibit, Radiological Society of North America, 2020
  • Rhode Island Society of Radiology Award, Warren Alpert Medical School of Brown University, 2017
  • Alpha Omega Alpha, Warren Alpert Medical School of Brown University, 2017
  • Certificate of Merit, Educational Exhibit, Radiological Society of North America, 2016
  • Baker Fellowship, Brown University, 2013
  • Sigma Xi, Brown University, 2013

Selected Publications

  1. Sujichantararat S, Biswas D, Kazerouni AS, Tsang ED, Sathe A, Hippe DS, Park VY, Chung M, Specht JM, Dintzis SM, Rahbar H, Holmes JH, Huang W, Partridge SC. Deep Learning-Based Synthetic Contrast-Enhanced Breast MRI for Monitoring Response to Neoadjuvant Therapy. Cancers (Basel). 2026 Jun 04; 18(11). View on PubMed
  2. Chung M. From Risk Prediction to Coordinated Care. AJR Am J Roentgenol. 2026 May 27. View on PubMed
  3. Chung M, Davis E, Greenwood H, Hayward J, Chou SS, Joe B, Strachowski L, Kelil T, Freimanis R, Price E, Ray K, Lee A, Yala A. Prospective deployment of AI-based risk stratification to enable expedited mammography workflow in a safety-net setting. NPJ Digit Med. 2026 May 18. View on PubMed
  4. Yeh D, Chung M. Artificial Intelligence as a Second Reader in a Simulation Study of Population-based Mammography Screening in the Netherlands. Radiol Imaging Cancer. 2026 May; 8(3):e269009. View on PubMed
  5. Bernstein MH, Chung M, Yala A, Baird GL. A novel statistical framework for quantifying risks and benefits of AI automation in screening mammography. PLOS Digit Health. 2026 Feb; 5(2):e0001231. View on PubMed
  6. Davis EE, Mark S, Woodard GA, Tang F, Gellatly M, Hayward JH, Ray KM, Joe BN, Lee AY, Chung M. Epinephrine-Containing Lidocaine and Hematoma Risk After Image-Guided Core-Needle Breast Biopsy. J Breast Imaging. 2025 Dec 13; 7(6):653-663. View on PubMed
  7. Liu L, Lian L, Hao Y, Pace A, Kim E, Homsi N, Pershad Y, Lai L, Gracie T, Kishtagari A, Carroll PR, Bick AG, Odisho AY, Chung M, Yala A. Human level information extraction from clinical reports with finetuned language models. Sci Rep. 2025 Nov 24; 15(1):45239. View on PubMed
  8. Wu X, Kolli KP, Mukhtar RA, Chung M, Joe BN, Kohlbrenner RM. Cryoablation Versus Breast-Conserving Surgery for Early-Stage, Low-Risk Breast Cancer ≤ 1.5 cm: A Cost-Effectiveness Analysis. Cardiovasc Intervent Radiol. 2026 Feb; 49(2):313-321. View on PubMed
  9. Srivastava D, Chung M. Simulation of Mammogram-based AI Triage of Intermediate-Risk Individuals for Breast MRI Screening. Radiol Imaging Cancer. 2025 Sep; 7(5):e259027. View on PubMed
  10. Vertido A, McKenzie T, Othieno A, Quirarte A, Kaur M, Abel MK, Chung M, Lee AY, Mukhtar RA. Accuracy of Breast MRI for Surgical Planning After Neoadjuvant Therapy for Patients with Invasive Lobular Carcinoma. Ann Surg Oncol. 2025 Nov; 32(12):8710-8719. View on PubMed
  11. Haver H, Bahl M, Chung M. Classifying the clinical significance of common breast pain symptoms using a large language model, ChatGPT (GPT-4). Clin Imaging. 2025 Sep; 125:110525. View on PubMed
  12. Chung M, Mongan J. Invited Commentary: Reflections on Prompt Engineering and Generative Artificial Intelligence in Radiology. Radiographics. 2025 04; 45(4):e240230. View on PubMed
  13. Chung M, Davari P. Feasibility of US-guided Core Needle Biopsy for Nipple Lesions. Radiol Imaging Cancer. 2025 Mar; 7(2):e259006. View on PubMed
  14. Dortilus A, Chung M. Potential of AI System to Enhance Early Breast Cancer Detection in Screening Mammography. Radiol Imaging Cancer. 2025 Jan; 7(1):e249027. View on PubMed
  15. Homsi N, Chung M. Patient Characteristics Impact False Positives in AI Interpretation of True-Negative Screening Breast Tomosynthesis Examinations. Radiol Imaging Cancer. 2024 09; 6(5):e249015. View on PubMed
  16. Chung M, Ton L, Lee AY. Forget Me Not: Incidental Findings on Breast MRI. J Breast Imaging. 2024 Jul 30; 6(4):430-448. View on PubMed
  17. Mittal S, Chung M. Assessment of AI Risk Scores on Screening Mammograms Preceding Breast Cancer Diagnosis. Radiol Imaging Cancer. 2024 05; 6(3):e249011. View on PubMed
  18. Xu K, Chung M, Hayward JH, Kelil T, Lee AY, Ray KM. MRI of the Lactating Breast. Radiographics. 2024 02; 44(2):e230129. View on PubMed
  19. Hastings-Robinson A, Chung M, Hayward JH, Ray KM, Price ER, Navarro R, Joe BN, Lee AY. The role of digital mammographic surveillance for detection of asymptomatic recurrence in autologous flap reconstructions. Clin Imaging. 2024 Feb; 106:110062. View on PubMed
  20. Ton L, Chung M. Updated Recommendations by the American College of Radiology for Breast Cancer Screening in Individuals at Higher-Than-Average Risk. Radiol Imaging Cancer. 2023 07; 5(4):e239015. View on PubMed

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