Eduardo Mortani-Barbosa, Jr., MD

Radiology
Accepting new patients
Sees patients age 18 and up
Headshot of Eduardo Mortani-Barbosa, Jr., MD
Penn Medicine Provider

About me

  • Associate Professor of Radiology at the Hospital of the University of Pennsylvania

My education and training

  • Medical School: University of Sao Paulo
  • Residency: University of Sao Paulo
  • Fellowship: University of Sao Paulo
  • Fellowship: University of Pennsylvania Health System

Spoken languages

English
English

Insurance accepted

Please contact the practice and/or the member services department of your insurance company for specific details before receiving services. Providers may participate in some, but not all, products offered by a health plan; providers may also accept plans at some practice locations but not others.

Penn Medicine hospital privileges

  • Hospital of the University of Pennsylvania: Has privileges to treat patients in the hospital.
  • Pennsylvania Hospital: Has privileges to treat patients in the hospital.
  • Penn Presbyterian Medical Center: Has privileges to treat patients in the hospital.
  • Penn Medicine Rittenhouse Long-Term Acute Care Hospital
  • Chester County Hospital: Has privileges to treat patients in the hospital.
Dr. Mortani-Barbosa is a Penn Medicine physician.

Qualifications and experience

Treatments and conditions

Research

Publications

Tianyu Han, Riga Wu, Yu Tian, Firas Khader, Lisa C. Adams, Keno K. Bressem, Christos Davatzikos, Jakob Nikolas Kather, Li Shen, David A. Mankoff, Eduardo Mortani Barbosa Jr, and Daniel Truhn CLEAR: An Auditable Foundation Model for Radiology Grounded in Clinical Concepts , Nature Biomedical Engineering: 2026


Eduardo Mortani Barbosa Jr Novel AI strategy of combining large dataset training, population specific retraining and confidence estimation to improve pulmonary nodule malignancy risk assessment , European Society of Thoracic Imaging Annual Meeting: 2026


Eduardo Mortani Barbosa Jr, Justin Shanahan, Alex Rupsee Combined feature sets of quantitative CT variables and clinical variables can outperform each set alone for AI driven classification of ILD (interstitial lung disease) against the gold standard MDD (multidisciplinary consensus) diagnosis , European Society of Thoracic Imaging Annual Meeting: 2026


Isabelle Christina Pappas, Quincy A. Hathaway, Hubert A. Gbate, Yashbir Singh, Elena Ghotbi, Friedrich D. Knollmann, Eduardo M. Barbosa Jr., Achala Donuru, Dongming Xu A 10-Year Comprehensive, Single-Center, Retrospective Analysis on Juxtapleural Nodules: Insights into Classification and Risk , Diagnostics: 2026


Mortani Barbosa EJ Jr. Radiologist fit in artificial intelligence–powered radiology services that are radiologist centered and patient centered: making radiologists relevant, valuable, and credible , ARRS (American Roentgen Ray Society): 2026


Zou C, Mankowski W, Pantalone L, Horng H, Setia Verma S, Mortani Barbosa EJ Jr, Cook TS, Noel PB, Carpenter EL, Thompson JC, Shinohara RT, Roshkovan L, Katz SI, Kontos D Transformer-based Fusion of Longitudinal Multimodal Radiomic Features from Chest Radiography and CT in COVID-19 , Radiology Artificial Intelligence , e240218: 2026


Tianyu Han, Riga Wu, Yu Tian, Firas Khader, Lisa C. Adams, Keno K. Bressem, Christos Davatzikos, Jakob Nikolas Kather, Li Shen, David A. Mankoff, Eduardo Mortani Barbosa Jr, and Daniel Truhn CLEAR: An Auditable Foundation Model for Radiology Grounded in Clinical Concepts , MedRxiv: 2026


Mortani Barbosa EJ Jr, Kim Y, Zhang Y, Setio AAA, Mellot F, Grenier PA, Zimmermann M, Georgescu B, Grbic S, Gefter WB Deep Learning–Based Pulmonary Nodule Risk Assessment Outperforms Established Malignancy Risk Scores in Lung Cancer Screening , Radiology Advances, 3(1): 2026


EB A novel AI strategy of combining large dataset training, population specific retraining and confidence estimation to improve classification performance in estimating pulmonary nodule malignancy risk , RSNA Annual Meeting, Chicago, IL: 2025


Eduardo Mortani Barbosa Jr, Yohan Kim, Warren Gefter, Bodgan Georgescu, Yanbo Zhang, Sasa Gbric Challenges in Generalizing DL Models for Lung Nodule Classification: Insights from Screening and High-Risk Biopsy-Proven Cohorts , European Society of Thoracic Imaging Annual Meeting: 2025