Eric K. Oermann

According to our database, Eric K. Oermann authored at least 21 papers between 2017 and 2024.

Collaborative distances:

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

2024

Concepts and applications of digital twins in healthcare and medicine.

Kang Zhang, Hong-Yu Zhou, Daniel T. Baptista-Hon, Yuanxu Gao, Xiaohong Liu, Eric K. Oermann, Sheng Xu, Shengwei Jin, Jian Zhang, Zhuo Sun, Yun Yin, Ronald M. Razmi, Alexandre Loupy, Stephan Beck, Jia Qu, Joseph Wu

Patterns, 2024

MedG-KRP: Medical Graph Knowledge Representation Probing.

Gabriel R. Rosenbaum, Lavender Yao Jiang, Ivaxi Sheth, Jaden Stryker, Anton Alyakin, Daniel Alexander Alber, Nicolas K. Goff, Young Joon Fred Kwon, John Markert, Mustafa Nasir-Moin, Jan Moritz Niehues, Karl L. Sangwon, Eunice Yang, Eric Karl Oermann

CoRR, 2024

MedMobile: A mobile-sized language model with expert-level clinical capabilities.

Krithik Vishwanath, Jaden Stryker, Anton Alyakin, Daniel Alexander Alber, Eric Karl Oermann

CoRR, 2024

HeadCT-ONE: Enabling Granular and Controllable Automated Evaluation of Head CT Radiology Report Generation.

Julián Nicolás Acosta, Xiaoman Zhang, Siddhant Dogra, Hong-Yu Zhou, Seyedmehdi Payabvash, Guido J. Falcone, Eric K. Oermann, Pranav Rajpurkar

CoRR, 2024

Refining Packing and Shuffling Strategies for Enhanced Performance in Generative Language Models.

Yanbing Chen, Ruilin Wang, Zihao Yang, Lavender Yao Jiang, Eric Karl Oermann

CoRR, 2024

Generalization in Healthcare AI: Evaluation of a Clinical Large Language Model.

Salman Rahman, Lavender Yao Jiang, Saadia Gabriel, Yindalon Aphinyanaphongs, Eric Karl Oermann, Rumi Chunara

CoRR, 2024

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

Making the Most Out of the Limited Context Length: Predictive Power Varies with Clinical Note Type and Note Section.

Hongyi Zheng, Yixin Zhu, Lavender Y. Jiang, Kyunghyun Cho, Eric K. Oermann

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, 2023

Intriguing Effect of the Correlation Prior on ICD-9 Code Assignment.

Zihao Yang, Chenkang Zhang, Muru Wu, Xujin Liu, Lavender Y. Jiang, Kyunghyun Cho, Eric K. Oermann

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, 2023

2022

Autoencoders for sample size estimation for fully connected neural network classifiers.

Faris F. Gulamali, Ashwin Sawant, Patricia H. Kovatch, Benjamin S. Glicksberg, Alexander Charney, Girish N. Nadkarni, Eric K. Oermann

npj Digit. Medicine, 2022

Language Model Classifier Aligns Better with Physician Word Sensitivity than XGBoost on Readmission Prediction.

Grace Yang, Ming Cao, Lavender Y. Jiang, Xujin Chris Liu, Alexander T. M. Cheung, Hannah Weiss, David Kurland, Kyunghyun Cho, Eric K. Oermann

CoRR, 2022

Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations.

Aahlad Manas Puli, Lily H. Zhang, Eric Karl Oermann, Rajesh Ranganath

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Identifying and mitigating bias in algorithms used to manage patients in a pandemic.

Yifan Li, Garrett Yoon, Mustafa Nasir-Moin, David Rosenberg, Sean Neifert, Douglas Kondziolka, Eric Karl Oermann

CoRR, 2021

Patient level simulation and reinforcement learning to discover novel strategies for treating ovarian cancer.

Brian Murphy, Mustafa Nasir-Moin, Grace von Oiste, Viola Chen, Howard Antony Riina, Douglas Kondziolka, Eric K. Oermann

CoRR, 2021

Stereo Video Reconstruction Without Explicit Depth Maps for Endoscopic Surgery.

Annika Brundyn, Jesse Swanson, Kyunghyun Cho, Doug Kondziolka, Eric K. Oermann

CoRR, 2021

Predictive Modeling in the Presence of Nuisance-Induced Spurious Correlations.

Aahlad Manas Puli, Lily H. Zhang, Eric K. Oermann, Rajesh Ranganath

CoRR, 2021

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

2019

CANDI: an R package and Shiny app for annotating radiographs and evaluating computer-aided diagnosis.

Marcus A. Badgeley, Manway Liu, Benjamin S. Glicksberg, Mark M. Shervey, John R. Zech, Khader Shameer, Joseph Lehar, Eric K. Oermann, Michael V. McConnell, Thomas M. Snyder, Joel T. Dudley

Bioinform., 2019

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