Publications by authors named "Stephen Pfohl"

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Toward expert-level medical question answering with large language models.
Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Stephen R Pfohl

Nat Med· March 2025

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Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations.
Joseph E Alderman, Joanne Palmer, Elinor Laws, Melissa D McCradden, Johan Ordish, Stephen R Pfohl

Lancet Digit Health· January 2025

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CANAIRI: the Collaboration for Translational Artificial Intelligence Trials in healthcare.
Melissa D McCradden, Alex John London, Judy Wawira Gichoya, Mark Sendak, Lauren Erdman, Stephen R Pfohl

Nat Med· January 2025

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A toolbox for surfacing health equity harms and biases in large language models.
Stephen R Pfohl, Heather Cole-Lewis, Rory Sayres, Darlene Neal, Mercy Asiedu

Nat Med· December 2024

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Health equity assessment of machine learning performance (HEAL): a framework and dermatology AI model case study.
Mike Schaekermann, Terry Spitz, Malcolm Pyles, Heather Cole-Lewis, Ellery Wulczyn, Stephen R Pfohl

EClinicalMedicine· April 2024

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An intentional approach to managing bias in general purpose embedding models.
Wei-Hung Weng, Andrew Sellergen, Atilla P Kiraly, Alexander D'Amour, Jungyeon Park, Stephen Pfohl

Lancet Digit Health· February 2024

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Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.
Joshua Lemmon, Lin Lawrence Guo, Ethan Steinberg, Keith E Morse, Scott Lanyon Fleming, Stephen R Pfohl

J Am Med Inform Assoc· November 2023

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The value of standards for health datasets in artificial intelligence-based applications.
Anmol Arora, Joseph E Alderman, Joanne Palmer, Shaswath Ganapathi, Elinor Laws, Stephen R Pfohl

Nat Med· November 2023

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Large language models encode clinical knowledge.
Karan Singhal, Shekoofeh Azizi, Tao Tu, S Sara Mahdavi, Jason Wei, Stephen Pfohl

Nature· August 2023

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Publisher Correction: Large language models encode clinical knowledge.
Karan Singhal, Shekoofeh Azizi, Tao Tu, S Sara Mahdavi, Jason Wei, Stephen Pfohl

Nature· August 2023

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Evaluation of Feature Selection Methods for Preserving Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine.
Joshua Lemmon, Lin Lawrence Guo, Jose Posada, Stephen R Pfohl, Jason Fries

Methods Inf Med· May 2023

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EHR foundation models improve robustness in the presence of temporal distribution shift.
Lin Lawrence Guo, Ethan Steinberg, Scott Lanyon Fleming, Jose Posada, Joshua Lemmon, Stephen R Pfohl

Sci Rep· March 2023

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Tackling bias in AI health datasets through the STANDING Together initiative.
Shaswath Ganapathi, Jo Palmer, Joseph E Alderman, Melanie Calvert, Cyrus Espinoza, Stephen R Pfohl

Nat Med· November 2022

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Considerations in the reliability and fairness audits of predictive models for advance care planning.
Jonathan Lu, Amelia Sattler, Samantha Wang, Ali Raza Khaki, Alison Callahan, Stephen Pfohl

Front Digit Health· September 2022

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Evaluating algorithmic fairness in the presence of clinical guidelines: the case of atherosclerotic cardiovascular disease risk estimation.
Agata Foryciarz, Stephen R Pfohl, Birju Patel, Nigam Shah

BMJ Health Care Inform· April 2022

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DLMM as a lossless one-shot algorithm for collaborative multi-site distributed linear mixed models.
Chongliang Luo, Md Nazmul Islam, Natalie E Sheils, John Buresh, Jenna Reps, Stephen R Pfohl

Nat Commun· March 2022

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Evaluation of domain generalization and adaptation on improving model robustness to temporal dataset shift in clinical medicine.
Lin Lawrence Guo, Stephen R Pfohl, Jason Fries, Alistair E W Johnson, Jose Posada

Sci Rep· February 2022

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A comparison of approaches to improve worst-case predictive model performance over patient subpopulations.
Stephen R Pfohl, Haoran Zhang, Yizhe Xu, Agata Foryciarz, Marzyeh Ghassemi

Sci Rep· February 2022

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Predictors of diagnostic transition from major depressive disorder to bipolar disorder: a retrospective observational network study.
Anastasiya Nestsiarovich, Jenna M Reps, Michael E Matheny, Scott L DuVall, Kristine E Lynch, Stephen R Pfohl

Transl Psychiatry· December 2021

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Learning decision thresholds for risk stratification models from aggregate clinician behavior.
Birju S Patel, Ethan Steinberg, Stephen R Pfohl, Nigam H Shah

J Am Med Inform Assoc· September 2021

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Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine.
Lin Lawrence Guo, Stephen R Pfohl, Jason Fries, Jose Posada, Scott Lanyon Fleming

Appl Clin Inform· August 2021

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An empirical characterization of fair machine learning for clinical risk prediction.
Stephen R Pfohl, Agata Foryciarz, Nigam H Shah

J Biomed Inform· January 2021

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Language models are an effective representation learning technique for electronic health record data.
Ethan Steinberg, Ken Jung, Jason A Fries, Conor K Corbin, Stephen R Pfohl

J Biomed Inform· January 2021

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Development and validation of a prognostic model predicting symptomatic hemorrhagic transformation in acute ischemic stroke at scale in the OHDSI network.
Qiong Wang, Jenna M Reps, Kristin Feeney Kostka, Patrick B Ryan, Yuhui Zou, Stephen R Pfohl

PLoS One· April 2020

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The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data.
Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C Kale, Kenneth Jung

Pac Symp Biocomput· August 2019

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