Mona Flores

According to our database, Mona Flores authored at least 16 papers between 2020 and 2024.

Collaborative distances:

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

2024

MONAI Label: A framework for AI-assisted interactive labeling of 3D medical images.

Andres Diaz-Pinto, Sachidanand Alle, Vishwesh Nath, Yucheng Tang, Alvin Ihsani, Muhammad Asad, Fernando Pérez-García, Pritesh Mehta, Wenqi Li, Mona Flores, Holger R. Roth, Tom Vercauteren, Daguang Xu, Prerna Dogra, Sébastien Ourselin, Andrew Feng, M. Jorge Cardoso

Medical Image Anal., 2024

Generative large language models are all-purpose text analytics engines: text-to-text learning is all your need.

Cheng Peng, Xi Yang, Aokun Chen, Zehao Yu, Kaleb E. Smith, Anthony B. Costa, Mona G. Flores, Jiang Bian, Yonghui Wu

J. Am. Medical Informatics Assoc., 2024

2023

Accelerating artificial intelligence: How federated learning can protect privacy, facilitate collaboration, and improve outcomes.

Malhar Patel, Ittai Dayan, Elliot K. Fishman, Mona Flores, Fiona J. Gilbert, Michal Guindy, Eugene J. Koay, Michael Rosenthal, Holger R. Roth, Marius George Linguraru

Health Informatics J., October, 2023

Do Gradient Inversion Attacks Make Federated Learning Unsafe?

Ali Hatamizadeh, Hongxu Yin, Pavlo Molchanov, Andriy Myronenko, Wenqi Li, Prerna Dogra, Andrew Feng, Mona G. Flores, Jan Kautz, Daguang Xu, Holger R. Roth

IEEE Trans. Medical Imaging, 2023

A study of generative large language model for medical research and healthcare.

Cheng Peng, Xi Yang, Aokun Chen, Kaleb E. Smith, Nima M. Pournejatian, Anthony B. Costa, Cheryl Martin, Mona G. Flores, Ying Zhang, Tanja Magoc, Gloria P. Lipori, Duane A. Mitchell, Naykky Singh Ospina, Mustafa M. Ahmed, William R. Hogan, Elizabeth A. Shenkman, Yi Guo, Jiang Bian, Yonghui Wu

npj Digit. Medicine, 2023

Health system-scale language models are all-purpose prediction engines.

Lavender Yao Jiang, Xujin Chris Liu, Nima Pour Nejatian, Mustafa Nasir-Moin, Duo Wang, Anas Z. Abidin, Kevin Eaton, Howard Antony Riina, Ilya Laufer, Paawan Punjabi, Madeline Miceli, Nora C. Kim, Cordelia Orillac, Zane Schnurman, Christopher Livia, Hannah Weiss, David Kurland, Sean Neifert, Yosef Dastagirzada, Douglas Kondziolka, Alexander T. M. Cheung, Grace Yang, Ming Cao, Mona Flores, Anthony B. Costa, Yindalon Aphinyanaphongs, Kyunghyun Cho, Eric Karl Oermann

Nat., 2023

NVIDIA FLARE: Federated Learning from Simulation to Real-World.

Holger R. Roth, Yan Cheng, Yuhong Wen, Isaac Yang, Ziyue Xu, Yuan-Ting Hsieh, Kristopher Kersten, Ahmed Harouni, Can Zhao, Kevin Lu, Zhihong Zhang, Wenqi Li, Andriy Myronenko, Dong Yang, Sean Yang, Nicola Rieke, Abood Quraini, Chester Chen, Daguang Xu, Nic Ma, Prerna Dogra, Mona Flores, Andrew Feng

IEEE Data Eng. Bull., 2023

2022

A large language model for electronic health records.

Xi Yang, Aokun Chen, Nima M. Pournejatian, Hoo Chang Shin, Kaleb E. Smith, Christopher Parisien, Colin Compas, Cheryl Martin, Anthony B. Costa, Mona G. Flores, Ying Zhang, Tanja Magoc, Christopher A. Harle, Gloria P. Lipori, Duane A. Mitchell, William R. Hogan, Elizabeth A. Shenkman, Jiang Bian, Yonghui Wu

npj Digit. Medicine, 2022

Rapid artificial intelligence solutions in a pandemic - The COVID-19-20 Lung CT Lesion Segmentation Challenge.

Holger R. Roth, Ziyue Xu, Carlos Tor-Díez, Ramon Sánchez-Jacob, Jonathan Zember, Jose Molto, Wenqi Li, Sheng Xu, Baris Turkbey, Evrim Turkbey, Dong Yang, Ahmed Harouni, Nicola Rieke, Shishuai Hu, Fabian Isensee, Claire Tang, Qinji Yu, Jan Sölter, Tong Zheng, Vitali Liauchuk, Ziqi Zhou, Jan Hendrik Moltz, Bruno Oliveira, Yong Xia, Klaus H. Maier-Hein, Qikai Li, Andreas Husch, Luyang Zhang, Vassili Kovalev, Li Kang, Alessa Hering, João L. Vilaça, Mona Flores, Daguang Xu, Bradford J. Wood, Marius George Linguraru

Medical Image Anal., 2022

MONAI: An open-source framework for deep learning in healthcare.

M. Jorge Cardoso, Wenqi Li, Richard Brown, Nic Ma, Eric Kerfoot, Yiheng Wang, Benjamin Murray, Andriy Myronenko, Can Zhao, Dong Yang, Vishwesh Nath, Yufan He, Ziyue Xu, Ali Hatamizadeh, Wentao Zhu, Yun Liu, Mingxin Zheng, Yucheng Tang, Isaac Yang, Michael Zephyr, Behrooz Hashemian, Sachidanand Alle, Mohammad Zalbagi Darestani, Charlie Budd, Marc Modat, Tom Vercauteren, Guotai Wang, Yiwen Li, Yipeng Hu, Yunguan Fu, Benjamin Gorman, Hans J. Johnson, Brad W. Genereaux, Barbaros S. Erdal, Vikash Gupta, Andres Diaz-Pinto, Andre Dourson, Lena Maier-Hein, Paul F. Jaeger, Michael Baumgartner, Jayashree Kalpathy-Cramer, Mona Flores, Justin S. Kirby, Lee A. D. Cooper, Holger R. Roth, Daguang Xu, David Bericat, Ralf Floca, S. Kevin Zhou, Haris Shuaib, Keyvan Farahani, Klaus H. Maier-Hein, Stephen R. Aylward, Prerna Dogra, Sébastien Ourselin, Andrew Feng

CoRR, 2022

GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records.

Xi Yang, Nima M. Pournejatian, Hoo Chang Shin, Kaleb E. Smith, Christopher Parisien, Colin Compas, Cheryl Martin, Mona G. Flores, Ying Zhang, Tanja Magoc, Christopher A. Harle, Gloria P. Lipori, Duane A. Mitchell, William R. Hogan, Elizabeth A. Shenkman, Jiang Bian, Yonghui Wu

CoRR, 2022

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

Deep Learning Based Automatic Detection of Adequately Positioned Mammograms.

Vikash Gupta, Clayton Taylor, Sarah Bonnet, Luciano M. Prevedello, Jeffrey Hawley, Richard D. White, Mona G. Flores, Barbaros Selnur Erdal

Proceedings of the Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health, 2021

2020

Deep Learning-Based Automatic Detection of Poorly Positioned Mammograms to Minimize Patient Return Visits for Repeat Imaging: A Real-World Application.

Vikash Gupta, Clayton Taylor, Sarah Bonnet, Luciano M. Prevedello, Jeffrey Hawley, Richard D. White, Mona G. Flores, Barbaros Selnur Erdal

CoRR, 2020

Democratizing Artificial Intelligence in Healthcare: A Study of Model Development Across Two Institutions Incorporating Transfer Learning.

Vikash Gupta, Holger Roth, Varun Buch, Marcio Aloisio Bezerra Cavalcanti Rockenbach, Richard D. White, Dong Yang, Olga Laur, Brian B. Ghoshhajra, Ittai Dayan, Daguang Xu, Mona G. Flores, Barbaros Selnur Erdal

CoRR, 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