Benjamin Goldstein

According to our database, Benjamin Goldstein authored at least 45 papers between 2013 and 2026.

Collaborative distances:

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

2026

Multimodal Training to Unimodal Deployment: Leveraging Unstructured Data During Training to Optimize Structured Data Only Deployment.

Zigui Wang, Minghui Sun, Jiang Shu, Matthew M. Engelhard, Lauren Franz, Benjamin Alan Goldstein

CoRR, March, 2026

NEST: Nested Event Stream Transformer for Sequences of Multisets.

Minghui Sun, Haoyu Gong, Xingyu You, Jillian H. Hurst, Benjamin Goldstein, Matthew Engelhard

CoRR, February, 2026

Discrete Time Neural Network Models to Address Time-Varying Predictor Importance: An Illustration in Predicting Mortality Over Different Time Horizons.

Mufan Wang, Matthew M. Engelhard, Patrick H. Pun, Benjamin Alan Goldstein

IEEE J. Biomed. Health Informatics, January, 2026

Comparing ambient scribes: a randomized crossover clinical trial addressing ambient scribe technologies' impact on physician burnout.

Anand Chowdhury, Michele Casey, Jonathan Wilson, Kathryn I. Pollak, Benjamin Goldstein, Armando Bedoya, Eric G. Poon

J. Am. Medical Informatics Assoc., 2026

2025

TRACER: Transfer Learning based Real-time Adaptation for Clinical Evolving Risk.

Mengying Yan, Ziye Tian, Siqi Li, Nan Liu, Benjamin Goldstein, Molei Liu, Chuan Hong

CoRR, December, 2025

FairPOT: Balancing AUC Performance and Fairness with Proportional Optimal Transport.

Pengxi Liu, Yi Shen, Matthew M. Engelhard, Benjamin Alan Goldstein, Michael J. Pencina, Nicoleta J. Economou-Zavlanos, Michael M. Zavlanos

CoRR, August, 2025

CLEAR: Unlearning Spurious Style-Content Associations with Contrastive LEarning with Anti-contrastive Regularization.

Minghui Sun, Benjamin Alan Goldstein, Matthew M. Engelhard

CoRR, July, 2025

Machine learning-based prediction models in medical decision-making in kidney disease: patient, caregiver, and clinician perspectives on trust and appropriate use.

Jessica Sperling, Whitney Welsh, Erin Haseley, Stella Quenstedt, Perusi B. Muhigaba, Adrian Brown, Patti Ephraim, Tariq Shafi, Michael Waitzkin, David J. Casarett, Benjamin Alan Goldstein

J. Am. Medical Informatics Assoc., 2025

Borrowing From the Future: Enhancing Early Risk Assessment through Contrastive Learning.

Minghui Sun, Matthew M. Engelhard, Benjamin Goldstein

Proceedings of the Machine Learning for Healthcare Conference (MLHC 2025), 2025

Predicting Partially Observed Long-Term Outcomes with Adversarial Positive-Unlabeled Domain Adaptation.

Mengying Yan, Meng Xia, Wei Angel Huang, Chuan Hong, Benjamin Goldstein, Matthew M. Engelhard

Proceedings of the Conference on Health, 2025

2024

Incorporating informatively collected laboratory data from EHR in clinical prediction models.

Minghui Sun, Matthew M. Engelhard, Armando Bedoya, Benjamin Goldstein

BMC Medical Informatics Decis. Mak., December, 2024

Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare.

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

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

A conditional multi-label model to improve prediction of a rare outcome: An illustration predicting autism diagnosis.

Wei A. Huang, Matthew Engelhard, Marika Coffman, Elliot D. Hill, Qin Weng, Abby Scheer, Gary Maslow, Ricardo Henao, Geraldine Dawson, Benjamin Alan Goldstein

J. Biomed. Informatics, 2024

Contrastive Learning for Clinical Outcome Prediction with Partial Data Sources.

Meng Xia, Jonathan Wilson, Benjamin Goldstein, Ricardo Henao

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

A roadmap to fair and trustworthy prediction model validation in healthcare.

Yilin Ning, Victor Volovici, Marcus Eng Hock Ong, Benjamin Alan Goldstein, Nan Liu

CoRR, 2023

Using natural language processing and structured medical data to phenotype patients hospitalized due to COVID-19.

Feier Chang, Jay Krishnan, Jillian H. Hurst, Michael E. Yarrington, Deverick J. Anderson, Emily C. O'Brien, Benjamin Alan Goldstein

CoRR, 2023

2022

Shapley variable importance cloud for interpretable machine learning.

Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Benjamin Alan Goldstein, Daniel Shu Wei Ting, Roger Vaughan, Nan Liu

Patterns, 2022

Predicting in-hospital length of stay: a two-stage modeling approach to account for highly skewed data.

Zhenhui Xu, Congwen Zhao, Charles D. Scales, Ricardo Henao, Benjamin Alan Goldstein

BMC Medical Informatics Decis. Mak., 2022

Correction to: Combining adult with pediatric patient data to develop a clinical decision support tool intended for children: leveraging machine learning to model heterogeneity.

Paul Sabharwal, Jillian H. Hurst, Rohit Tejwani, Kevin T. Hobbs, Jonathan C. Routh, Benjamin Alan Goldstein

BMC Medical Informatics Decis. Mak., 2022

Combining adult with pediatric patient data to develop a clinical decision support tool intended for children: leveraging machine learning to model heterogeneity.

Paul Sabharwal, Jillian H. Hurst, Rohit Tejwani, Kevin T. Hobbs, Jonathan C. Routh, Benjamin Alan Goldstein

BMC Medical Informatics Decis. Mak., 2022

Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models.

Jillian H. Hurst, Congwen Zhao, Haley P. Hostetler, Mohsen Ghiasi Gorveh, Jason E. Lang, Benjamin Alan Goldstein

BMC Medical Informatics Decis. Mak., 2022

AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data.

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

J. Biomed. Informatics, 2022

AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.

Feng Xie, Yilin Ning, Han Yuan, Benjamin Alan Goldstein, Marcus Eng Hock Ong, Nan Liu, Bibhas Chakraborty

J. Biomed. Informatics, 2022

Observability and its impact on differential bias for clinical prediction models.

Mengying Yan, Michael J. Pencina, L. Ebony Boulware, Benjamin Alan Goldstein

J. Am. Medical Informatics Assoc., 2022

A framework for the oversight and local deployment of safe and high-quality prediction models.

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

J. Am. Medical Informatics Assoc., 2022

2021

Shapley variable importance clouds for interpretable machine learning.

Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Benjamin Alan Goldstein, Daniel Shu Wei Ting, Roger Vaughan, Nan Liu

CoRR, 2021

Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer.

Junya Chen, Zidi Xiu, Benjamin Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Understanding Algorithmic Bias in Clinical Prediction Models.

Mengying Yan, Michael J. Pencina, Benjamin Alan Goldstein

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

Comparison of a patient cohort and predictive models derived from local academic medical centers versus a national health database.

Courtney Page, Conrad Sweitek, Cliona Molony, Karen Chandross, Benjamin Alan Goldstein

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

Variational Disentanglement for Rare Event Modeling.

Zidi Xiu, Chenyang Tao, Michael Gao, Connor Davis, Benjamin Alan Goldstein, Ricardo Henao

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Identified themes of interactive visualizations overlayed onto EHR data: an example of improving birth center operating room efficiency.

Andrew Stirling, Tracy Tubb, Emily S. Reiff, Chad A. Grotegut, Jennifer Gagnon, Weiyi Li, Gail Bradley, Eric G. Poon, Benjamin Alan Goldstein

J. Am. Medical Informatics Assoc., 2020

Supercharging Imbalanced Data Learning With Causal Representation Transfer.

Junya Chen, Zidi Xiu, Benjamin Alan Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao

CoRR, 2020

2019

How and when informative visit processes can bias inference when using electronic health records data for clinical research.

Benjamin Alan Goldstein, Matthew Phelan, Neha J. Pagidipati, Sarah B. Peskoe

J. Am. Medical Informatics Assoc., 2019

An outcome model approach to transporting a randomized controlled trial results to a target population.

Benjamin Alan Goldstein, Matthew Phelan, Neha J. Pagidipati, Rury R. Holman, Michael J. Pencina, Elizabeth A. Stuart

J. Am. Medical Informatics Assoc., 2019

2018

Designing risk prediction models for ambulatory no-shows across different specialties and clinics.

Xiruo Ding, Ziad Gellad, III Chad Mather, Pamela Barth, Eric G. Poon, Mark Newman, Benjamin Alan Goldstein

J. Am. Medical Informatics Assoc., 2018

Adversarial Time-to-Event Modeling.

Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Courtney Page, Benjamin Alan Goldstein, Lawrence Carin, Ricardo Henao

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

Lessons Learned from an EHR-Based Population Health Datamart: Southeastern Diabetes Initiative (SEDI).

Ursula A. Rogers, Shelley A. Rusincovitch, Matthew Phelan, Nigel B. Neely, Benjamin Alan Goldstein

Proceedings of the AMIA 2018, 2018

2017

Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus.

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

J. Am. Medical Informatics Assoc., 2017

Predicting mortality over different time horizons: which data elements are needed?

Benjamin Alan Goldstein, Michael J. Pencina, Maria E. Montez-Rath, Wolfgang C. Winkelmayer

J. Am. Medical Informatics Assoc., 2017

Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.

Benjamin Alan Goldstein, Ann Marie Navar, Michael J. Pencina, John P. A. Ioannidis

J. Am. Medical Informatics Assoc., 2017

Informed Presence Bias in the Analysis of Electronic Health Records.

Benjamin Alan Goldstein, Matthew Phelan, Nrupen Bhavsar

Proceedings of the Summit on Clinical Research Informatics, 2017

2016

A Systematic Review of Using Electronic Heath Records to Predict Clinical Events: Assessment of Opportunities and Challenges.

Benjamin Alan Goldstein, Ann Marie Navar, Michael J. Pencina, John P. A. Ioannidis

Proceedings of the Summit on Clinical Research Informatics, 2016

2015

Classifying individuals based on a densely captured sequence of vital signs: An example using repeated blood pressure measurements during hemodialysis treatment.

Benjamin Alan Goldstein, Tara I. Chang, Wolfgang C. Winkelmayer

J. Biomed. Informatics, 2015

A Simulation Framework for Longitudinal Electronic Health Records Data.

Matthew Phelan, Benjamin Alan Goldstein

Proceedings of the AMIA 2015, 2015

2013

Changes during dialysis captured in electronic health records help predict near-term risk of sudden cardiac death.

Benjamin Alan Goldstein, Wolfgang C. Winkelmayer, Themistocles L. Assimes

Proceedings of the AMIA 2013, 2013