A Systematic Study of Race and Sex Bias in CNN-Based Cardiac MR Segmentation. - Tiarna Lee; Esther Puyol-Antón; Bram Ruijsink; Miaojing Shi; Andrew P. King (STACOM@MICCAI, 2022)

An Investigation into Race Bias in Random Forest Models Based on Breast DCE-MRI Derived Radiomics Features. - Mohamed Huti; Tiarna Lee; Elinor Sawyer; Andrew P. King (CLIP/FAIMI/EPIMI@MICCAI, 2023)

An Investigation into the Impact of Deep Learning Model Choice on Sex and Race Bias in Cardiac MR Segmentation. - Tiarna Lee; Esther Puyol-Antón; Bram Ruijsink; Keana Aitcheson; Miaojing Shi; Andrew P. King (CLIP/FAIMI/EPIMI@MICCAI, 2023)

RAISE - Radiology AI Safety, an End-to-end lifecycle approach. - M. Jorge Cardoso; Julia Moosbauer; Tessa Sundaram Cook; Barbaros Selnur Erdal; Brad W. Genereaux; Vikash Gupta; Bennett A. Landman; Tiarna Lee; Parashkev Nachev; Elanchezhian Somasundaram; Ronald M. Summers; Khaled Younis; et al. (CoRR, 2023)

An investigation into the causes of race bias in AI-based cine CMR segmentation. - Tiarna Lee; Esther Puyol-Antón; Bram Ruijsink; Sebastien Roujol; Theodore Barfoot; Shaheim Ogbomo-Harmitt; Miaojing Shi; Andrew P. King (CoRR, 2024)

Does a Rising Tide Lift All Boats? Bias Mitigation for AI-based CMR Segmentation. - Tiarna Lee; Esther Puyol-Antón; Bram Ruijsink; Miaojing Shi; Andrew P. King (CoRR, 2025)

Themed Challenges to Solve Data Scarcity in Africa: A Proposition for Increasing Local Data Collection and Integration. - Mubaraq Yakubu; Udunna Anazodo; Maruf Adewole; Theodore Barfoot; Tiarna Lee; Tom Vercauteren; Jonathan Shapey; Andrew P. King; Alexander Hammers (CoRR, 2025)