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)

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)

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)

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 (ML4H@NeurIPS, 2020)

The Utility of General Domain Transfer Learning for Medical Language Tasks. - Daniel Ranti; Katie Hanss; Shan Zhao 004; Varun Arvind; Joseph J. Titano; Anthony B. Costa; Eric K. Oermann (CoRR, 2020)

Predictive Modeling in the Presence of Nuisance-Induced Spurious Correlations. - Aahlad Manas Puli; Lily H. Zhang; Eric K. Oermann; Rajesh Ranganath (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)

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)

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)

Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations. - Aahlad Manas Puli; Lily H. Zhang; Eric Karl Oermann; Rajesh Ranganath (ICLR, 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)

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)

Intriguing Effect of the Correlation Prior on ICD-9 Code Assignment. - Zihao Yang 001; Chenkang Zhang; Muru Wu; Xujin Liu 001; Lavender Y. Jiang; Kyunghyun Cho; Eric K. Oermann (ACL (student), 2023)

Making the Most Out of the Limited Context Length: Predictive Power Varies with Clinical Note Type and Note Section. - Hongyi Zheng; Yixin Zhu 002; Lavender Y. Jiang; Kyunghyun Cho; Eric K. Oermann (ACL (student), 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; et al. (Nat., 2023)

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)

Refining Packing and Shuffling Strategies for Enhanced Performance in Generative Language Models. - Yanbing Chen; Ruilin Wang; Zihao Yang 001; Lavender Yao Jiang; 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)

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; et al. (CoRR, 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; et al. (Patterns, 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 Karl Oermann; Pranav Rajpurkar (CHIL, 2025)

Repurposing the scientific literature with vision-language models. - Anton Alyakin; Jaden Stryker; Daniel Alexander Alber; Karl L. Sangwon; Brandon Duderstadt; Akshay Save; David Kurland; Spencer Frome; Shrutika Singh; Jeff Zhang 004; Eunice Yang; Ki Yun Park; et al. (CoRR, 2025)

BPQA Dataset: Evaluating How Well Language Models Leverage Blood Pressures to Answer Biomedical Questions. - Chi Hang; Ruiqi Deng; Lavender Yao Jiang; Zihao Yang 001; Anton Alyakin; Daniel Alber; Eric Karl Oermann (CoRR, 2025)

It is Too Many Options: Pitfalls of Multiple-Choice Questions in Generative AI and Medical Education. - Shrutika Singh; Anton Alyakin; Daniel Alexander Alber; Jaden Stryker; Ai Phuong S. Tong; Karl L. Sangwon; Nicolas K. Goff; Mathew de la Paz; Miguel Hernandez-Rovira; Ki Yun Park; Eric Claude Leuthardt; Eric Karl Oermann (CoRR, 2025)

Medical large language models are easily distracted. - Krithik Vishwanath; Anton Alyakin; Daniel Alexander Alber; Jin Vivian Lee; Douglas Kondziolka; Eric Karl Oermann (CoRR, 2025)

Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations. - Yu-Hsiang Lan; Eric K. Oermann (CoRR, 2025)

Evaluating the performance and fragility of large language models on the self-assessment for neurological surgeons. - Krithik Vishwanath; Anton Alyakin; Mrigayu Ghosh; Jin Vivian Lee; Daniel Alexander Alber; Karl L. Sangwon; Douglas Kondziolka; Eric Karl Oermann (CoRR, 2025)

Clinically Grounded Agent-based Report Evaluation: An Interpretable Metric for Radiology Report Generation. - Radhika Dua; Young Joon Fred Kwon; Siddhant Dogra; Daniel Freedman; Diana Ruan; Motaz Nashawaty; Danielle Rigau; Daniel Alexander Alber; Kang Zhang; Kyunghyun Cho; Eric Karl Oermann (CoRR, 2025)