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Kirti Magudia

Assistant Professor in the Department of Radiology
Radiology, Abdominal Imaging
Department of Radiology, DUMC 3808, Durham, NC 27710
Department of Radiology, 3808 DUMC, Durham, NC 27710

Overview


Kirti Magudia, MD, PhD is an Assistant Professor of Radiology at Duke University School of Medicine. She completed fellowship in abdominal imaging and ultrasound at the University of California, San Francisco and Diagnostic Radiology Residency at Brigham & Women's Hospital. Her research centers on high-level applications of machine learning in radiology, including CT-based body composition analysis and prostate MR, which was facilitated by 7 dedicated months at the MGH/BWH Center for Clinical Data Science and a year long T32 research fellowship in the Biomedical Imaging for Clinical Scientists Program at UCSF. She was the founding resident chair of the Brigham and Women’s Hospital Women in the Radiology Program and has extensively advocated for family-friendly trainee policies. Dr. Magudia is a graduate of the Tri-institutional MD/PhD program of Weill Cornell, Sloan-Kettering, and Rockefeller University, where she completed her Ph.D. in cell and cancer biology in the laboratory of Alan Hall developing a novel 3D cell culture model of colon tumorigenesis.

Current Appointments & Affiliations


Assistant Professor in the Department of Radiology · 2021 - Present Radiology, Abdominal Imaging, Radiology

Recent Publications


Open-Weight Language Models and Retrieval Augmented Generation for Automated Structured Data Extraction from Diagnostic Reports: Assessment of Approaches and Parameters.

Journal Article Radiol Artif Intell · March 12, 2025 "Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note th ... Full text Link to item Cite

RSNA 2023 Abdominal Trauma AI Challenge: Review and Outcomes.

Journal Article Radiol Artif Intell · January 2025 Purpose To evaluate the performance of the winning machine learning models from the 2023 RSNA Abdominal Trauma Detection AI Challenge. Materials and Methods The competition was hosted on Kaggle and took place between July 26 and October 15, 2023. The multi ... Full text Link to item Cite
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