Eric K. Oermann

16 papers Journal 13Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Paradox of De-identification: A Critique of HIPAA Safe Harbour in the Age of LLMs. CoRR Lavender Y. Jiang, Xujin Chris Liu, Kyunghyun Cho, Eric K. Oermann
2025	J	`jnl`	Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations. CoRR Yu-Hsiang Lan, Eric K. Oermann
2024	J	`jnl`	Concepts and applications of digital twins in healthcare and medicine. Patterns 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
2024	J	`jnl`	HeadCT-ONE: Enabling Granular and Controllable Automated Evaluation of Head CT Radiology Report Generation. CoRR Julián N. Acosta, Xiaoman Zhang, Siddhant Dogra, Hong-Yu Zhou, Seyedmehdi Payabvash, Guido J. Falcone, Eric K. Oermann, Pranav Rajpurkar
2023	—	`conf`	Intriguing Effect of the Correlation Prior on ICD-9 Code Assignment. ACL (student) Zihao Yang, Chenkang Zhang, Muru Wu, Xujin Liu, Lavender Y. Jiang, Kyunghyun Cho, Eric K. Oermann
2023	—	`conf`	Making the Most Out of the Limited Context Length: Predictive Power Varies with Clinical Note Type and Note Section. ACL (student) Hongyi Zheng, Yixin Zhu, Lavender Y. Jiang, Kyunghyun Cho, Eric K. Oermann
2022	J	`jnl`	Autoencoders for sample size estimation for fully connected neural network classifiers. npj Digit. Medicine Faris F. Gulamali, Ashwin Sawant, Patricia H. Kovatch, Benjamin S. Glicksberg, Alexander Charney, Girish N. Nadkarni, Eric K. Oermann
2022	J	`jnl`	Language Model Classifier Aligns Better with Physician Word Sensitivity than XGBoost on Readmission Prediction. CoRR Grace Yang, Ming Cao, Lavender Y. Jiang, Xujin Chris Liu, Alexander T. M. Cheung, Hannah Weiss, David Kurland, Kyunghyun Cho, Eric K. Oermann
2021	J	`jnl`	Patient level simulation and reinforcement learning to discover novel strategies for treating ovarian cancer. CoRR Brian Murphy, Mustafa Nasir-Moin, Grace von Oiste, Viola Chen, Howard Antony Riina, Douglas Kondziolka, Eric K. Oermann
2021	J	`jnl`	Predictive Modeling in the Presence of Nuisance-Induced Spurious Correlations. CoRR Aahlad Manas Puli, Lily H. Zhang, Eric K. Oermann, Rajesh Ranganath
2021	J	`jnl`	Stereo Video Reconstruction Without Explicit Depth Maps for Endoscopic Surgery. CoRR Annika Brundyn, Jesse Swanson, Kyunghyun Cho, Doug Kondziolka, Eric K. Oermann
2020	—	`conf`	Appropriate Evaluation of Diagnostic Utility of Machine Learning Algorithm Generated Images. ML4H@NeurIPS 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
2020	J	`jnl`	The Utility of General Domain Transfer Learning for Medical Language Tasks. CoRR Daniel Ranti, Katie Hanss, Shan Zhao, Varun Arvind, Joseph J. Titano, Anthony B. Costa, Eric K. Oermann
2019	J	`jnl`	CANDI: an R package and Shiny app for annotating radiographs and evaluating computer-aided diagnosis. Bioinform. 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
2018	J	`jnl`	Confounding variables can degrade generalization performance of radiological deep learning models. CoRR John R. Zech, Marcus A. Badgeley, Manway Liu, Anthony B. Costa, Joseph J. Titano, Eric K. Oermann
2017	J	`jnl`	Wide and deep volumetric residual networks for volumetric image classification. CoRR Varun Arvind, Anthony B. Costa, Marcus A. Badgeley, Samuel K. Cho, Eric K. Oermann