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An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction.

S. Pfohl, A. Foryciarz, and N. Shah. CoRR, (2020)

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Stephen R Freedman

Stephen R. Piccolo

Stephen R Goodwin

Gerhard Pfohl

Michael Pfohl

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An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction.S. Pfohl, A. Foryciarz, and N. Shah. CoRR, (2020)Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data.E. Steinberg, K. Jung, J. Fries, C. Corbin, S. Pfohl, and N. Shah. CoRR, (2020)Transfer learning to adapt predictive models for pediatric patients in the EHR.S. Pfohl, and N. Shah. AMIA, AMIA, (2018)Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine.L. Guo, S. Pfohl, J. Fries, J. Posada, S. Fleming, C. Aftandilian, N. Shah, and L. Sung. Appl. Clin. Inform., 12 (4): 808-815 (2021)An empirical characterization of fair machine learning for clinical risk prediction.S. Pfohl, A. Foryciarz, and N. Shah. J. Biomed. Informatics, (2021)Language models are an effective representation learning technique for electronic health record data.E. Steinberg, K. Jung, J. Fries, C. Corbin, S. Pfohl, and N. Shah. J. Biomed. Informatics, (2021)Adapting to Latent Subgroup Shifts via Concepts and Proxies.I. Alabdulmohsin, N. Chiou, A. D'Amour, A. Gretton, S. Koyejo, M. Kusner, S. Pfohl, O. Salaudeen, J. Schrouff, and K. Tsai. AISTATS, volume 206 of Proceedings of Machine Learning Research, page 9637-9661. PMLR, (2023)Counterfactual Reasoning for Fair Clinical Risk Prediction.S. Pfohl, T. Duan, D. Ding, and N. Shah. MLHC, volume 106 of Proceedings of Machine Learning Research, page 325-358. PMLR, (2019)Adapting to Latent Subgroup Shifts via Concepts and Proxies.I. Alabdulmohsin, N. Chiou, A. D'Amour, A. Gretton, S. Koyejo, M. Kusner, S. Pfohl, O. Salaudeen, J. Schrouff, and K. Tsai. CoRR, (2022)Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.J. Lemmon, L. Guo, E. Steinberg, K. Morse, S. Fleming, C. Aftandilian, S. Pfohl, J. Posada, N. Shah, J. Fries and 1 other author(s). J. Am. Medical Informatics Assoc., 30 (12): 2004-2011 (November 2023)

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Disambiguation of "Pfohl, Stephen R."

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An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction.

Please choose a person to relate this publication to

Stephen R Freedman

Stephen R. Piccolo

Stephen R Goodwin

Gerhard Pfohl

Michael Pfohl

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Pfohl, Stephen R."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction.

Please choose a person to relate this publication to

Stephen R Freedman

Stephen R. Piccolo

Stephen R Goodwin

Gerhard Pfohl

Michael Pfohl

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction.