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ORCIDBenjamin Goldstein 0001
Person information
- affiliation: Duke University, Department of Biomedical Engineering, Durham, NC, USA
Other persons with the same name
- Benjamin Goldstein — disambiguation page
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Journal Articles
- 2024
[j18]Nicoleta J. Economou-Zavlanos
, Sophia Bessias, Michael P. Cary, Armando Bedoya, Benjamin Goldstein, John Eric Jelovsek, Cara O'Brien, Nancy Walden, Matthew Elmore, Amanda B. Parrish, Scott Elengold, Kay S. Lytle, Suresh Balu, Michael E. Lipkin, Afreen Idris Shariff, Michael Gao, David Leverenz, Ricardo Henao, David Y. Ming, David M. Gallagher, Michael J. Pencina, Eric G. Poon:
Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare. J. Am. Medical Informatics Assoc. 31(3): 705-713 (2024)- 2022
- [j17]Mengying Yan, Michael J. Pencina, L. Ebony Boulware, Benjamin Alan Goldstein:
Observability and its impact on differential bias for clinical prediction models. J. Am. Medical Informatics Assoc. 29(5): 937-943 (2022) - [j16]Armando Bedoya, Nicoleta J. Economou-Zavlanos, Benjamin Alan Goldstein, Allison Young, John Eric Jelovsek, Cara O'Brien, Amanda B. Parrish, Scott Elengold, Kay Lytle, Suresh Balu, Erich Huang, Eric G. Poon, Michael J. Pencina:
A framework for the oversight and local deployment of safe and high-quality prediction models. J. Am. Medical Informatics Assoc. 29(9): 1631-1636 (2022) - [j15]Feng Xie, Yilin Ning, Han Yuan, Benjamin Alan Goldstein, Marcus Eng Hock Ong, Nan Liu, Bibhas Chakraborty:
AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data. J. Biomed. Informatics 125: 103959 (2022) - [j14]Han Yuan, Feng Xie, Marcus Eng Hock Ong, Yilin Ning, Marcel Lucas Chee, Seyed Ehsan Saffari, Hairil Rizal Abdullah, Benjamin Alan Goldstein, Bibhas Chakraborty, Nan Liu:
AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data. J. Biomed. Informatics 129: 104072 (2022) - [j13]Paul Sabharwal, Jillian H. Hurst, Rohit Tejwani, Kevin T. Hobbs, Jonathan C. Routh, Benjamin Alan Goldstein:
Combining adult with pediatric patient data to develop a clinical decision support tool intended for children: leveraging machine learning to model heterogeneity. BMC Medical Informatics Decis. Mak. 22(1): 84 (2022) - [j12]Jillian H. Hurst, Congwen Zhao, Haley P. Hostetler, Mohsen Ghiasi Gorveh, Jason E. Lang, Benjamin Alan Goldstein:
Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models. BMC Medical Informatics Decis. Mak. 22(1): 108 (2022) - [j11]Zhenhui Xu, Congwen Zhao, Charles D. Scales, Ricardo Henao, Benjamin Alan Goldstein:
Predicting in-hospital length of stay: a two-stage modeling approach to account for highly skewed data. BMC Medical Informatics Decis. Mak. 22(1): 110 (2022) - [j10]Paul Sabharwal, Jillian H. Hurst, Rohit Tejwani, Kevin T. Hobbs, Jonathan C. Routh, Benjamin Alan Goldstein:
Correction to: Combining adult with pediatric patient data to develop a clinical decision support tool intended for children: leveraging machine learning to model heterogeneity. BMC Medical Informatics Decis. Mak. 22(1): 128 (2022) - [j9]Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Benjamin Alan Goldstein, Daniel Shu Wei Ting, Roger Vaughan, Nan Liu:
Shapley variable importance cloud for interpretable machine learning. Patterns 3(4): 100452 (2022) - 2020
- [j8]Andrew Stirling, Tracy Tubb, Emily S. Reiff, Chad A. Grotegut, Jennifer Gagnon, Weiyi Li, Gail Bradley, Eric G. Poon, Benjamin Alan Goldstein:
Identified themes of interactive visualizations overlayed onto EHR data: an example of improving birth center operating room efficiency. J. Am. Medical Informatics Assoc. 27(5): 783-787 (2020) - 2019
- [j7]Benjamin Alan Goldstein, Matthew Phelan, Neha J. Pagidipati, Rury R. Holman, Michael J. Pencina, Elizabeth A. Stuart:
An outcome model approach to transporting a randomized controlled trial results to a target population. J. Am. Medical Informatics Assoc. 26(5): 429-437 (2019) - [j6]Benjamin Alan Goldstein, Matthew Phelan, Neha J. Pagidipati, Sarah B. Peskoe:
How and when informative visit processes can bias inference when using electronic health records data for clinical research. J. Am. Medical Informatics Assoc. 26(12): 1609-1617 (2019) - 2018
- [j5]Xiruo Ding, Ziad Gellad, III Chad Mather, Pamela Barth, Eric G. Poon, Mark Newman, Benjamin Alan Goldstein:
Designing risk prediction models for ambulatory no-shows across different specialties and clinics. J. Am. Medical Informatics Assoc. 25(8): 924-930 (2018) - 2017
- [j4]Benjamin Alan Goldstein, Michael J. Pencina, Maria E. Montez-Rath, Wolfgang C. Winkelmayer:
Predicting mortality over different time horizons: which data elements are needed? J. Am. Medical Informatics Assoc. 24(1): 176-181 (2017) - [j3]Benjamin Alan Goldstein, Ann Marie Navar, Michael J. Pencina, John P. A. Ioannidis:
Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review. J. Am. Medical Informatics Assoc. 24(1): 198-208 (2017) - [j2]Susan E. Spratt, Katherine Pereira, Bradi B. Granger, Bryan C. Batch, Matthew Phelan, Michael J. Pencina, Marie Lynn Miranda, L. Ebony Boulware, Joseph E. Lucas, Charlotte L. Nelson, Benjamin Neely, Benjamin Alan Goldstein, Pamela Barth, Rachel L. Richesson, Isaretta L. Riley, Leonor Corsino, Eugenia R. McPeek Hinz, Shelley A. Rusincovitch, Jennifer Green, Anna Beth Barton, Carly Kelley, Kristen Hyland, Monica Tang, Amanda Elliott, Ewa Ruel, Alexander Clark, Melanie Mabrey, Kay Lyn Morrissey, Jyothi Rao, Beatrice Hong, Marjorie Pierre-Louis, Katherine Kelly, Nicole E. Jelesoff:
Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus. J. Am. Medical Informatics Assoc. 24(e1): e121-e128 (2017) - 2015
- [j1]Benjamin Alan Goldstein, Tara I. Chang, Wolfgang C. Winkelmayer:
Classifying individuals based on a densely captured sequence of vital signs: An example using repeated blood pressure measurements during hemodialysis treatment. J. Biomed. Informatics 57: 219-224 (2015)
Conference and Workshop Papers
- 2021
- [c10]Zidi Xiu, Chenyang Tao, Michael Gao, Connor Davis, Benjamin Alan Goldstein, Ricardo Henao:
Variational Disentanglement for Rare Event Modeling. AAAI 2021: 10469-10477 - [c9]Courtney Page, Conrad Sweitek, Cliona Molony, Karen Chandross, Benjamin Alan Goldstein:
Comparison of a patient cohort and predictive models derived from local academic medical centers versus a national health database. AMIA 2021 - [c8]Mengying Yan, Michael J. Pencina, Benjamin Alan Goldstein:
Understanding Algorithmic Bias in Clinical Prediction Models. AMIA 2021 - [c7]Junya Chen, Zidi Xiu, Benjamin Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao:
Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer. NeurIPS 2021: 21229-21243 - 2018
- [c6]Ursula A. Rogers, Shelley A. Rusincovitch, Matthew Phelan, Nigel B. Neely, Benjamin Alan Goldstein:
Lessons Learned from an EHR-Based Population Health Datamart: Southeastern Diabetes Initiative (SEDI). AMIA 2018 - [c5]Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Courtney Page, Benjamin Alan Goldstein, Lawrence Carin, Ricardo Henao:
Adversarial Time-to-Event Modeling. ICML 2018: 734-743 - 2017
- [c4]Benjamin Alan Goldstein, Matthew Phelan, Nrupen Bhavsar:
Informed Presence Bias in the Analysis of Electronic Health Records. CRI 2017 - 2016
- [c3]Benjamin Alan Goldstein, Ann Marie Navar, Michael J. Pencina, John P. A. Ioannidis:
A Systematic Review of Using Electronic Heath Records to Predict Clinical Events: Assessment of Opportunities and Challenges. CRI 2016 - 2015
- [c2]Matthew Phelan, Benjamin Alan Goldstein:
A Simulation Framework for Longitudinal Electronic Health Records Data. AMIA 2015 - 2013
- [c1]Benjamin Alan Goldstein, Wolfgang C. Winkelmayer, Themistocles L. Assimes:
Changes during dialysis captured in electronic health records help predict near-term risk of sudden cardiac death. AMIA 2013
Informal and Other Publications
- 2023
- [i8]Feier Chang, Jay Krishnan, Jillian H. Hurst, Michael E. Yarrington, Deverick J. Anderson, Emily C. O'Brien, Benjamin Alan Goldstein:
Using natural language processing and structured medical data to phenotype patients hospitalized due to COVID-19. CoRR abs/2302.01536 (2023) - [i7]Yilin Ning, Victor Volovici, Marcus Eng Hock Ong, Benjamin Alan Goldstein, Nan Liu:
A roadmap to fair and trustworthy prediction model validation in healthcare. CoRR abs/2304.03779 (2023) - 2021
- [i6]Feng Xie, Yilin Ning, Han Yuan, Benjamin Alan Goldstein, Marcus Eng Hock Ong, Nan Liu, Bibhas Chakraborty:
AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data. CoRR abs/2106.06957 (2021) - [i5]Han Yuan, Feng Xie, Marcus Eng Hock Ong, Yilin Ning, Marcel Lucas Chee, Seyed Ehsan Saffari, Hairil Rizal Abdullah, Benjamin Alan Goldstein, Bibhas Chakraborty, Nan Liu:
AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data. CoRR abs/2107.06039 (2021) - [i4]Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Benjamin Alan Goldstein, Daniel Shu Wei Ting, Roger Vaughan, Nan Liu:
Shapley variable importance clouds for interpretable machine learning. CoRR abs/2110.02484 (2021) - 2020
- [i3]Zidi Xiu, Chenyang Tao, Michael Gao, Connor Davis, Benjamin Alan Goldstein, Ricardo Henao:
Variational Disentanglement for Rare Event Modeling. CoRR abs/2009.08541 (2020) - [i2]Junya Chen, Zidi Xiu, Benjamin Alan Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao:
Supercharging Imbalanced Data Learning With Causal Representation Transfer. CoRR abs/2011.12454 (2020) - 2018
- [i1]Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Courtney Page, Benjamin Alan Goldstein, Lawrence Carin, Ricardo Henao:
Adversarial Time-to-Event Modeling. CoRR abs/1804.03184 (2018)
Coauthor Index
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