Jesse Tetreault

According to our database, Jesse Tetreault authored at least 2 papers between 2020 and 2021.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2021

Federated learning improves site performance in multicenter deep learning without data sharing.

Karthik V. Sarma, Stephanie A. Harmon, Thomas Sanford, Holger R. Roth, Ziyue Xu, Jesse Tetreault, Daguang Xu, Mona G. Flores, Alex G. Raman, Rushikesh Kulkarni, Bradford J. Wood, Peter L. Choyke, Alan Priester, Leonard S. Marks, Steven S. Raman, Dieter Enzmann, Baris Turkbey, William Speier, Corey W. Arnold

J. Am. Medical Informatics Assoc., 2021

2020

Federated Learning for Breast Density Classification: A Real-World Implementation.

Holger R. Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C. Bizzo, Yuhong Wen, Varun Buch, Meesam Shah, Felipe Kitamura, Matheus Mendonça, Vitor Lavor, Ahmed Harouni, Colin Compas, Jesse Tetreault, Prerna Dogra, Yan Cheng, Selnur Erdal, Richard D. White, Behrooz Hashemian, Thomas J. Schultz, Miao Zhang, Adam McCarthy, B. Min Yun, Elshaimaa Sharaf, Katharina Viktoria Hoebel, Jay B. Patel, Bryan Chen, Sean Ko, Evan Leibovitz, Etta D. Pisano, Laura Coombs, Daguang Xu, Keith J. Dreyer, Ittai Dayan, Ram C. Naidu, Mona Flores, Daniel L. Rubin, Jayashree Kalpathy-Cramer

Proceedings of the Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning, 2020