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2020 – today
- 2023
[c4]Elizabeth Bondi-Kelly
, Thomas Hartvigsen, Lindsay M. Sanneman, Swami Sankaranarayanan, Zach Harned, Grace Wickerson, Judy Wawira Gichoya, Lauren Oakden-Rayner, Leo Anthony Celi, Matthew P. Lungren, Julie A. Shah, Marzyeh Ghassemi:
Taking Off with AI: Lessons from Aviation for Healthcare. EAAMO 2023: 4:1-4:14- [c3]Melissa D. McCradden, Oluwadara Odusi, Shalmali Joshi, Ismail Akrout, Kagiso Ndlovu, Ben Glocker, Gabriel Maicas, Xiaoxuan Liu, Mjaye Mazwi, Tee Garnett, Lauren Oakden-Rayner, Myrtede Alfred, Irvine Sihlahla, Oswa Shafei, Anna Goldenberg:
What's fair is... fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning: JustEFAB. FAccT 2023: 1505-1519 - [c2]Minyan Zeng, Yutong Xie, Minh-Son To, Lauren Oakden-Rayner, Luke Whitbread, Stephen Bacchi, Alix Bird, Luke Smith, Rebecca Scroop, Timothy Kleinig, Jim Jannes, Lyle J. Palmer, Mark Jenkinson:
Improved Flexibility and Interpretability of Large Vessel Stroke Prognostication Using Image Synthesis and Multi-task Learning. MICCAI (5) 2023: 696-705 - 2022
- [c1]Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Pfohl, Marzyeh Ghassemi:
Improving the Fairness of Chest X-ray Classifiers. CHIL 2022: 204-233 - [i1]Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Robert Pfohl, Marzyeh Ghassemi:
Improving the Fairness of Chest X-ray Classifiers. CoRR abs/2203.12609 (2022)
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