Benjamin Alan Goldstein - researchr alias

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Viewing Publication 1 - 13 from 13

2025

Machine learning-based prediction models in medical decision-making in kidney disease: patient, caregiver, and clinician perspectives on trust and appropriate useJessica Sperling, Whitney Welsh, Erin Haseley, Stella Quenstedt, Perusi B. Muhigaba, Adrian Brown, Patti Ephraim, Tariq Shafi, Michael Waitzkin, David J. Casarett, Benjamin Alan Goldstein. jamia, 32(1):51-62, 2025. [doi]

2024

A conditional multi-label model to improve prediction of a rare outcome: An illustration predicting autism diagnosisWei A. Huang, Matthew Engelhard, Marika Coffman, Elliot D. Hill, Qin Weng, Abby Scheer, Gary Maslow, Ricardo Henao, Geraldine Dawson, Benjamin Alan Goldstein. jbi, 157:104711, 2024. [doi]

2022

A framework for the oversight and local deployment of safe and high-quality prediction modelsArmando 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. jamia, 29(9):1631-1636, 2022. [doi]

Environmental and clinical data utility in pediatric asthma exacerbation risk prediction modelsJillian H. Hurst, Congwen Zhao, Haley P. Hostetler, Mohsen Ghiasi Gorveh, Jason E. Lang, Benjamin Alan Goldstein. midm, 22(1):108, 2022. [doi]

Shapley variable importance cloud for interpretable machine learningYilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Benjamin Alan Goldstein, Daniel Shu Wei Ting, Roger Vaughan, Nan Liu 0003. patterns, 3(4):100452, 2022. [doi]

Correction to: Combining adult with pediatric patient data to develop a clinical decision support tool intended for children: leveraging machine learning to model heterogeneityPaul Sabharwal, Jillian H. Hurst, Rohit Tejwani, Kevin T. Hobbs, Jonathan C. Routh, Benjamin Alan Goldstein. midm, 22(1):128, 2022. [doi]

Combining adult with pediatric patient data to develop a clinical decision support tool intended for children: leveraging machine learning to model heterogeneityPaul Sabharwal, Jillian H. Hurst, Rohit Tejwani, Kevin T. Hobbs, Jonathan C. Routh, Benjamin Alan Goldstein. midm, 22(1):84, 2022. [doi]

AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival dataFeng Xie, Yilin Ning, Han Yuan, Benjamin Alan Goldstein, Marcus Eng Hock Ong, Nan Liu 0003, Bibhas Chakraborty. jbi, 125:103959, 2022. [doi]

Predicting in-hospital length of stay: a two-stage modeling approach to account for highly skewed dataZhenhui Xu, Congwen Zhao, Charles D. Scales, Ricardo Henao, Benjamin Alan Goldstein. midm, 22(1):110, 2022. [doi]

Observability and its impact on differential bias for clinical prediction modelsMengying Yan, Michael J. Pencina, L. Ebony Boulware, Benjamin Alan Goldstein. jamia, 29(5):937-943, 2022. [doi]

AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events dataHan 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 0003. jbi, 129:104072, 2022. [doi]

2021

Comparison of a patient cohort and predictive models derived from local academic medical centers versus a national health databaseCourtney Page, Conrad Sweitek, Cliona Molony, Karen Chandross, Benjamin Alan Goldstein. amia 2021: [doi]

Understanding Algorithmic Bias in Clinical Prediction ModelsMengying Yan, Michael J. Pencina, Benjamin Alan Goldstein. amia 2021: [doi]

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