1 citations · 4 across the 8 of their papers we have counts for
3 papers · 1 filter
RAISE -- Radiology AI Safety, an End-to-end lifecycle approach
M. Jorge Cardoso, Julia Moosbauer, Tessa S. Cook +11
The integration of AI into radiology introduces opportunities for improved clinical care provision and efficiency but it demands a meticulous approach to mitigate potential risks a…
An Investigation Into Race Bias in Random Forest Models Based on Breast DCE-MRI Derived Radiomics Features
Mohamed Huti, Tiarna Lee, Elinor Sawyer +1
Recent research has shown that artificial intelligence (AI) models can exhibit bias in performance when trained using data that are imbalanced by protected attribute(s). Most work…
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 +3
In medical imaging, artificial intelligence (AI) is increasingly being used to automate routine tasks. However, these algorithms can exhibit and exacerbate biases which lead to dis…