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Eric K. Oermann
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2020 – today
- 2024
- [j4]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:
Concepts and applications of digital twins in healthcare and medicine. Patterns 5(8): 101028 (2024) - [i13]Salman Rahman, Lavender Yao Jiang, Saadia Gabriel, Yindalon Aphinyanaphongs, Eric Karl Oermann, Rumi Chunara:
Generalization in Healthcare AI: Evaluation of a Clinical Large Language Model. CoRR abs/2402.10965 (2024) - [i12]Yanbing Chen, Ruilin Wang, Zihao Yang, Lavender Yao Jiang, Eric Karl Oermann:
Refining Packing and Shuffling Strategies for Enhanced Performance in Generative Language Models. CoRR abs/2408.09621 (2024) - [i11]Julián Nicolás Acosta, Xiaoman Zhang, Siddhant Dogra, Hong-Yu Zhou, Seyedmehdi Payabvash, Guido J. Falcone, Eric K. Oermann, Pranav Rajpurkar:
HeadCT-ONE: Enabling Granular and Controllable Automated Evaluation of Head CT Radiology Report Generation. CoRR abs/2409.13038 (2024) - [i10]Krithik Vishwanath, Jaden Stryker, Anton Alyakin, Daniel Alexander Alber, Eric Karl Oermann:
MedMobile: A mobile-sized language model with expert-level clinical capabilities. CoRR abs/2410.09019 (2024) - 2023
- [j3]Lavender Yao Jiang
, Xujin Chris Liu, Nima Pour Nejatian, Mustafa Nasir-Moin
Health system-scale language models are all-purpose prediction engines. Nat. 619(7969): 357-362 (2023) - [c4]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: 104-108 - [c3]Zihao Yang
Intriguing Effect of the Correlation Prior on ICD-9 Code Assignment. ACL (student) 2023: 109-118 - [i9]Hongyi Zheng, Yixin Zhu, Lavender Yao Jiang, Kyunghyun Cho, Eric Karl Oermann:
Making the Most Out of the Limited Context Length: Predictive Power Varies with Clinical Note Type and Note Section. CoRR abs/2307.07051 (2023) - 2022
- [j2]Faris F. Gulamali
Autoencoders for sample size estimation for fully connected neural network classifiers. npj Digit. Medicine 5 (2022) - [c2]Aahlad Manas Puli, Lily H. Zhang, Eric Karl Oermann, Rajesh Ranganath:
Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations. ICLR 2022 - [i8]Grace Yang, Ming Cao, Lavender Y. Jiang, Xujin Chris 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 abs/2211.07047 (2022) - 2021
- [i7]Aahlad Manas Puli, Lily H. Zhang, Eric K. Oermann, Rajesh Ranganath:
Predictive Modeling in the Presence of Nuisance-Induced Spurious Correlations. CoRR abs/2107.00520 (2021) - [i6]Annika Brundyn, Jesse Swanson, Kyunghyun Cho, Doug Kondziolka, Eric K. Oermann:
Stereo Video Reconstruction Without Explicit Depth Maps for Endoscopic Surgery. CoRR abs/2109.08227 (2021) - [i5]Brian Murphy, Mustafa Nasir-Moin, Grace von Oiste, Viola Chen, Howard Antony Riina, Douglas Kondziolka, Eric K. Oermann:
Patient level simulation and reinforcement learning to discover novel strategies for treating ovarian cancer. CoRR abs/2110.11872 (2021) - [i4]Yifan Li, Garrett Yoon, Mustafa Nasir-Moin, David Rosenberg, Sean Neifert, Douglas Kondziolka, Eric Karl Oermann:
Identifying and mitigating bias in algorithms used to manage patients in a pandemic. CoRR abs/2111.00340 (2021) - 2020
- [c1]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: 179-193 - [i3]Daniel Ranti
The Utility of General Domain Transfer Learning for Medical Language Tasks. CoRR abs/2002.06670 (2020)
2010 – 2019
- 2019
- [j1]Marcus A. Badgeley
CANDI: an R package and Shiny app for annotating radiographs and evaluating computer-aided diagnosis. Bioinform. 35(9): 1610-1612 (2019) - 2018
- [i2]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 abs/1807.00431 (2018) - 2017
- [i1]Varun Arvind, Anthony B. Costa
Wide and deep volumetric residual networks for volumetric image classification. CoRR abs/1710.01217 (2017)
Coauthor Index
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