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Scott J. Hebbring
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2020 – today
- 2022
- [j4]Andrea H. Ramirez
, Lina M. Sulieman
, David J. Schlueter, Alese E. Halvorson
, Jun Qian, Francis Ratsimbazafy, Roxana Loperena-Cortes, Kelsey R. Mayo, Melissa A. Basford
, Nicole Deflaux
, Karthik Muthuraman, Karthik Natarajan, Abel N. Kho
, Hua Xu, Consuelo H. Wilkins, Hoda Anton-Culver, Eric Boerwinkle, Mine Cicek, Cheryl R. Clark
, Elizabeth Cohn, Lucila Ohno-Machado, Sheri D. Schully, Brian K. Ahmedani, Maria Argos, Robert M. Cronin
, Christopher J. O'Donnell, Mona Fouad, David B. Goldstein, Philip Greenland
, Scott J. Hebbring, Elizabeth W. Karlson, Parinda Khatri
, Bruce Korf
, Jordan W. Smoller
, Stephen Sodeke
, John Wilbanks, Justin Hentges, Stephen Mockrin, Christopher Lunt
, Stephanie A. Devaney, Kelly Gebo, Joshua C. Denny
, Robert J. Carroll
, David Glazer
, Paul A. Harris
, George Hripcsak, Anthony A. Philippakis, Dan M. Roden
:
The All of Us Research Program: Data quality, utility, and diversity. Patterns 3(8): 100570 (2022) - 2021
- [j3]Xiayuan Huang
, Nicholas P. Tatonetti, Katie Larow, Brooke Delgoffee, John Mayer, David Page, Scott J. Hebbring:
E-Pedigrees: a large-scale automatic family pedigree prediction application. Bioinform. 37(21): 3966-3968 (2021) - [c3]Daehee Kim, Stephanie Gamboa, Vanessa Hernandez, Marlen Martinez-Lopez, Scott J. Hebbring, John Mayer, Jamie Fox:
Medical Big Data Analysis System to Discover Associations between Genetic Variants and Diseases. ICC 2021: 1-6 - 2020
- [i2]Alexander K. Taylor, Ross Kleiman, Scott J. Hebbring, Peggy L. Peissig, David Page:
High-Throughput Approach to Modeling Healthcare Costs Using Electronic Healthcare Records. CoRR abs/2011.09497 (2020)
2010 – 2019
- 2019
- [c2]Xinyuan Zhang, Yogasudha Veturi, Shefali Setia Verma, William Bone, Anurag Verma, Anastasia Lucas, Scott J. Hebbring, Joshua C. Denny, Ian B. Stanaway, Gail P. Jarvik, David R. Crosslin, Eric B. Larson, Laura Rasmussen-Torvik, Sarah A. Pendergrass, Jordan W. Smoller, Hakon Hakonarson, Patrick Sleiman, Chunhua Weng, David Fasel, Wei-Qi Wei, Iftikhar J. Kullo, Daniel J. Schaid, Wendy K. Chung, Marylyn D. Ritchie:
Detecting potential pleiotropy across cardiovascular and neurological diseases using univariate, bivariate, and multivariate methods on 43, 870 individuals from the eMERGE network. PSB 2019: 272-283 - [i1]Ross S. Kleiman, Paul S. Bennett, Peggy L. Peissig, Richard L. Berg, Zhaobin Kuang, Scott J. Hebbring, Michael D. Caldwell, David Page:
High-Throughput Machine Learning from Electronic Health Records. CoRR abs/1907.01901 (2019) - 2018
- [j2]Xiayuan Huang
, Robert C. Elston, Guilherme J. M. Rosa
, John Mayer, Zhan Ye, Terrie E. Kitchner, Murray H. Brilliant, David Page, Scott J. Hebbring
:
Applying family analyses to electronic health records to facilitate genetic research. Bioinform. 34(4): 635-642 (2018) - [c1]Xiayuan Huang, Robert C. Elston, John Mayer, Zhan Ye, Yuqi He, David Page, Scott J. Hebbring:
Use of Electronic Health Record to Predict Family Relationships for Phenome-wide Research. AMIA 2018 - 2015
- [j1]Scott J. Hebbring, Majid Rastegar-Mojarad, Zhan Ye, John Mayer, Crystal Jacobson, Simon M. Lin:
Application of clinical text data for phenome-wide association studies (PheWASs). Bioinform. 31(12): 1981-1987 (2015)
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last updated on 2024-08-05 21:11 CEST by the dblp team
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