Improving the Fairness of Chest X-ray Classifiers. - Haoran Zhang 003; Natalie Dullerud; Karsten Roth; Lauren Oakden-Rayner; Stephen Pfohl; Marzyeh Ghassemi (CHIL, 2022)

Taking Off with AI: Lessons from Aviation for Healthcare. - 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 (EAAMO, 2023)

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. - 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; et al. (FAccT, 2023)

Improved Flexibility and Interpretability of Large Vessel Stroke Prognostication Using Image Synthesis and Multi-task Learning. - Minyan Zeng; Yutong Xie 001; Minh-Son To; Lauren Oakden-Rayner; Luke Whitbread; Stephen Bacchi; Alix Bird; Luke Smith; Rebecca Scroop; Timothy Kleinig; Jim Jannes; Lyle J. Palmer; et al. (MICCAI (5), 2023)

Can an accurate model be bad? - Melissa D. McCradden; Mjaye L. Mazwi; Lauren Oakden-Rayner (Patterns, 2025)