Brian D. Williamson

According to our database, Brian D. Williamson authored at least 10 papers between 2018 and 2024.

Collaborative distances:

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

2024

Data-driven automated classification algorithms for acute health conditions: applying PheNorm to COVID-19 disease.

Joshua C. Smith, Brian D. Williamson, David J. Cronkite, Daniel Park, Jill M. Whitaker, Michael F. McLemore, Joshua Osmanski, Robert Winter, Arvind Ramaprasan, Ann Kelley, Mary Shea, Saranrat Wittayanukorn, Danijela Stojanovic, Yueqin Zhao, Sengwee Toh, Kevin B. Johnson, David Aronoff, David S. Carrell

J. Am. Medical Informatics Assoc., February, 2024

Importance of variables from different time frames for predicting self-harm using health system data.

Charles J. Wolock, Brian D. Williamson, Susan M. Shortreed, Gregory E. Simon, Karen J. Coleman, Rodney Yeargans, Brian K. Ahmedani, Yihe G. Daida, Frances L. Lynch, Rebecca C. Rossom, Rebecca A. Ziebell, Maricela Cruz, Robert D. Wellman, R. Yates Coley

J. Biomed. Informatics, 2024

A general framework for developing computable clinical phenotype algorithms.

David S. Carrell, James S. Floyd, Susan Gruber, Brian L. Hazlehurst, Patrick J. Heagerty, Jennifer C. Nelson, Brian D. Williamson, Robert Ball

J. Am. Medical Informatics Assoc., 2024

2023

Practical considerations for variable screening in the Super Learner.

Brian D. Williamson, Drew King, Ying Huang

CoRR, 2023

2022

rigr: Regression, Inference, and General Data Analysis Tools in R.

Yiqun T. Chen, Brian D. Williamson, Taylor Okonek, Charles J. Wolock, Andrew J. Spieker, Travis Y. Hee Wai, James P. Hughes, Scott S. Emerson, Amy Willis

J. Open Source Softw., December, 2022

2021

Super LeArner Prediction of NAb Panels (SLAPNAP): a containerized tool for predicting combination monoclonal broadly neutralizing antibody sensitivity.

Brian D. Williamson, Craig A. Magaret, Peter B. Gilbert, Sohail Nizam, Courtney Simmons, David C. Benkeser

Bioinform., November, 2021

Improving random forest predictions in small datasets from two-phase sampling designs.

Sunwoo Han, Brian D. Williamson, Youyi Fong

BMC Medical Informatics Decis. Mak., 2021

2020

Efficient nonparametric statistical inference on population feature importance using Shapley values.

Brian D. Williamson, Jean Feng

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Prediction of VRC01 neutralization sensitivity by HIV-1 gp160 sequence features.

Craig A. Magaret, David C. Benkeser, Brian D. Williamson, Bhavesh Borate, Lindsay N. Carpp, Ivelin S. Georgiev, Ian Setliff, Adam S. Dingens, Noah Simon, Marco Carone, Christopher Simpkins, David C. Montefiori, Galit Alter, Wen-Han Yu, Michal Juraska, Paul Thatcher Edlefsen, Shelly Karuna, Nyaradzo M. Mgodi, Srilatha Edugupanti, Peter B. Gilbert

PLoS Comput. Biol., 2019

2018

Nonparametric variable importance using an augmented neural network with multi-task learning.

Jean Feng, Brian D. Williamson, Marco Carone, Noah Simon

Proceedings of the 35th International Conference on Machine Learning, 2018