Eric K. Oermann

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 12

Top Topics

Sas Enterprise Miner

Machine Learning

Top Venues

Publications

Hongyi Zheng, Yixin Zhu, Lavender Y. Jiang, Kyunghyun Cho, Eric K. Oermann
Making the Most Out of the Limited Context Length: Predictive Power Varies with Clinical Note Type and Note Section. ACL (student) (2023)
Zihao Yang, Chenkang Zhang, Muru Wu, Xujin Liu, Lavender Y. Jiang, Kyunghyun Cho, Eric K. Oermann
Intriguing Effect of the Correlation Prior on ICD-9 Code Assignment. ACL (student) (2023)
Grace Yang, Ming Cao, Lavender Y. Jiang, Xujin C. Liu, Alexander T. M. Cheung, Hannah Weiss, David Kurland, Kyunghyun Cho, Eric K. Oermann
Language Model Classifier Aligns Better with Physician Word Sensitivity than XGBoost on Readmission Prediction. CoRR (2022)
Faris F. Gulamali, Ashwin Sawant, Patricia A. Kovatch, Benjamin S. Glicksberg, Alexander Charney, Girish N. Nadkarni, Eric K. Oermann
Autoencoders for sample size estimation for fully connected neural network classifiers. npj Digit. Medicine 5 (2022)
Aahlad Manas Puli, Lily H. Zhang, Eric K. Oermann, Rajesh Ranganath
Predictive Modeling in the Presence of Nuisance-Induced Spurious Correlations. CoRR (2021)
Brian Murphy, Mustafa Nasir-Moin, Grace von Oiste, Viola Chen, Howard A. Riina, Douglas Kondziolka, Eric K. Oermann
Patient level simulation and reinforcement learning to discover novel strategies for treating ovarian cancer. CoRR (2021)
Annika Brundyn, Jesse Swanson, Kyunghyun Cho, Doug Kondziolka, Eric K. Oermann
Stereo Video Reconstruction Without Explicit Depth Maps for Endoscopic Surgery. CoRR (2021)
Daniel Ranti, Katie Hanss, Shan Zhao, Varun Arvind, Joseph J. Titano, Anthony B. Costa, Eric K. Oermann
The Utility of General Domain Transfer Learning for Medical Language Tasks. CoRR (2020)
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
Appropriate Evaluation of Diagnostic Utility of Machine Learning Algorithm Generated Images. ML4H@NeurIPS (2020)
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
CANDI: an R package and Shiny app for annotating radiographs and evaluating computer-aided diagnosis. Bioinform. 35 (9) (2019)
John R. Zech, Marcus A. Badgeley, Manway Liu, Anthony B. Costa, Joseph J. Titano, Eric K. Oermann
Confounding variables can degrade generalization performance of radiological deep learning models. CoRR (2018)
Varun Arvind, Anthony B. Costa, Marcus A. Badgeley, Samuel K. Cho, Eric K. Oermann
Wide and deep volumetric residual networks for volumetric image classification. CoRR (2017)