Anthony B. Costa

According to our database, Anthony B. Costa authored at least 13 papers between 2013 and 2026.

Collaborative distances:

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

2026

Fold-CP: A Context Parallelism Framework for Biomolecular Modeling.

Dejun Lin, Simon K. S. Chu, Vishanth Iyer, Youhan Lee, John St. John, Kevin Boyd, Brian Roland, Xiaowei Ren, Guoqing Zhou, Zhonglin Cao, Polina Binder, Yuliya Zhautouskaya, Jakub Zakrzewski, Maximilian Stadler, Kyle Gion, Yuxing Peng, Xi Chen, Tianjing Zhang, Philipp Junk, Michelle Dimon, Pawel Gniewek, Fabian Ortega, McKinley Polen, Ivan Grubisic, Ali Bashir, Graham Holt, Danny Kovtun, Matthias Grass, Luca Naef, Rui Wang, Jian Peng, Anthony B. Costa, Saee Paliwal, Eddie Calleja, Timur Rvachov, Neha Tadimeti, Roy Tal, Emine Küçükbenli

CoRR, March, 2026

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

BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery.

Peter St. John, Dejun Lin, Polina Binder, Malcolm Greaves, Vega Shah, John St. John, Adrian Lange, Patrick D. Hsu, Rajesh Illango, Arvind Ramanathan, Anima Anandkumar, David H. Brookes, Akosua Busia, Abhishaike Mahajan, Stephen Malina, Neha Prasad, Sam Sinai, Lindsay Edwards, Thomas Gaudelet, Cristian Regep, Martin Steinegger, Burkhard Rost, Alexander Brace, Kyle Hippe, Luca Naef, Keisuke Kamata, George Armstrong, Kevin Boyd, Zhonglin Cao, Han-Yi Chou, Simon Chu, Allan dos Santos Costa, Sajad Darabi, Eric Dawson, Kieran Didi, Cong Fu, Mario Geiger, Michelle Gill, Darren Hsu, Gagan Kaushik, Maria Korshunova, Steven Kothen-Hill, Youhan Lee, Meng Liu, Micha Livne, Zachary McClure, Jonathan Mitchell, Alireza Moradzadeh, Ohad Mosafi, Youssef Nashed, Saee Paliwal, Yuxing Peng, Sara Rabhi, Farhad Ramezanghorbani, Danny Reidenbach, Camir Ricketts, Brian Roland, Kushal Shah, Tyler Shimko, Hassan Sirelkhatim, Savitha Srinivasan, Abraham C. Stern, Dorota Toczydlowska, Srimukh Prasad Veccham, Niccolò Alberto Elia Venanzi, Anton Vorontsov, Jared Wilber, Isabel Wilkinson, Wei Jing Wong, Eva Xue, Cory Ye, Xin Yu, Yang Zhang, Guoqing Zhou, Becca Zandstein, Christian Dallago, Bruno Trentini, Emine Küçükbenli, Timur Rvachov, Eddie Calleja, Johnny Israeli, Harry Clifford, Risto Haukioja, Nicholas Haemel, Kyle Tretina, Neha Tadimeti, Anthony B. Costa

CoRR, 2024

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

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

2020

The Utility of General Domain Transfer Learning for Medical Language Tasks.

Daniel Ranti, Katie Hanss, Shan Zhao, Varun Arvind, Joseph J. Titano, Anthony B. Costa, Eric K. Oermann

CoRR, 2020

Appropriate Evaluation of Diagnostic Utility of Machine Learning Algorithm Generated Images.

Young Joon Kwon, Danielle Toussie, Lea Azour, Jose Concepcion, Corey Eber, G. Anthony Reina, Ping Tak Peter Tang, Amish H. Doshi, Eric K. Oermann, Anthony B. Costa

Proceedings of the Machine Learning for Health Workshop, 2020

2018

Confounding variables can degrade generalization performance of radiological deep learning models.

John R. Zech, Marcus A. Badgeley, Manway Liu, Anthony B. Costa, Joseph J. Titano, Eric K. Oermann

CoRR, 2018

2017

Wide and deep volumetric residual networks for volumetric image classification.

Varun Arvind, Anthony B. Costa, Marcus A. Badgeley, Samuel K. Cho, Eric K. Oermann

CoRR, 2017

2015

Beacon: Deployment and Application of Intel Xeon Phi Coprocessorsfor Scientific Computing.

R. Glenn Brook, Alexander Heinecke, Anthony B. Costa, Paul Peltz Jr., Vincent C. Betro, Troy Baer, Michael Bader, Pradeep Dubey

Comput. Sci. Eng., 2015

Operator experience determines performance in a simulated computer-based brain tumor resection task.

Terrell Holloway, Zachary S. Lorsch, Michael A. Chary, Stanislaw Sobotka, Maximillian M. Moore, Anthony B. Costa, Rolando F. Del Maestro, Joshua Bederson

Int. J. Comput. Assist. Radiol. Surg., 2015

2013

Extending the length and time scales of Gram-Schmidt Lyapunov vector computations.

Anthony B. Costa, Jason R. Green

J. Comput. Phys., 2013