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Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks.

B. Nestor, M. McDermott, W. Boag, G. Berner, T. Naumann, M. Hughes, A. Goldenberg, and M. Ghassemi. MLHC, volume 106 of Proceedings of Machine Learning Research, page 381-405. PMLR, (2019)

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Marzyeh Ghassemi

Alireza Ghassemi

Other publications of authors with the same name

Racial Disparities and Mistrust in End-of-Life Care.W. Boag, H. Suresh, L. Celi, P. Szolovits, and M. Ghassemi. MLHC, volume 85 of Proceedings of Machine Learning Research, page 587-602. PMLR, (2018)Machine Learning for Health (ML4H) Workshop at NeurIPS 2018.N. Antropova, A. Beam, B. Beaulieu-Jones, I. Chen, C. Chivers, A. Dalca, S. Finlayson, M. Fiterau, J. Fries, M. Ghassemi and 8 other author(s). CoRR, (2018)Machine learning and health need better values.M. Ghassemi, and S. Mohamed. npj Digit. Medicine, (2022)Semi-Markov Offline Reinforcement Learning for Healthcare.M. Fatemi, M. Wu, J. Petch, W. Nelson, S. Connolly, A. Benz, A. Carnicelli, and M. Ghassemi. CHIL, volume 174 of Proceedings of Machine Learning Research, page 119-137. PMLR, (2022)SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness.N. Ng, K. Cho, and M. Ghassemi. EMNLP (1), page 1268-1283. Association for Computational Linguistics, (2020)Multiple Sclerosis Severity Classification From Clinical Text.A. Costa, S. Denkovski, M. Malyska, S. Moon, B. Rufino, Z. Yang, T. Killian, and M. Ghassemi. ClinicalNLP@EMNLP, page 7-23. Association for Computational Linguistics, (2020)In the Name of Fairness: Assessing the Bias in Clinical Record De-identification.Y. Xiao, S. Lim, T. Pollard, and M. Ghassemi. FAccT, page 123-137. ACM, (2023)Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings.V. Suriyakumar, N. Papernot, A. Goldenberg, and M. Ghassemi. FAccT, page 723-734. ACM, (2021)The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations.A. Balagopalan, H. Zhang, K. Hamidieh, T. Hartvigsen, F. Rudzicz, and M. Ghassemi. FAccT, page 1194-1206. ACM, (2022)Improving Mutual Information Estimation with Annealed and Energy-Based Bounds.R. Brekelmans, S. Huang, M. Ghassemi, G. Steeg, R. Grosse, and A. Makhzani. ICLR, OpenReview.net, (2022)

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Disambiguation of "Ghassemi, Marzyeh"

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Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks.

Please choose a person to relate this publication to

Marzyeh Ghassemi

Alireza Ghassemi

Alireza Ghassemi

Alireza Ghassemi

Alireza Ghassemi

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Ghassemi, Marzyeh"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks.

Please choose a person to relate this publication to

Marzyeh Ghassemi

Alireza Ghassemi

Alireza Ghassemi

Alireza Ghassemi

Alireza Ghassemi

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks.