264 citations · 488 across the 10 of their papers we have counts for
4 papers · 1 filter
RadEdit: stress-testing biomedical vision models via diffusion image editing
Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez +11
Biomedical imaging datasets are often small and biased, meaning that real-world performance of predictive models can be substantially lower than expected from internal testing. Thi…
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
Shruthi Bannur, Stephanie Hyland, Qianchu Liu +13
Self-supervised learning in vision-language processing exploits semantic alignment between imaging and text modalities. Prior work in biomedical VLP has mostly relied on the alignm…
Making the Most of Text Semantics to Improve Biomedical Vision--Language Processing
Benedikt Boecking, Naoto Usuyama, Shruthi Bannur +9
Multi-modal data abounds in biomedicine, such as radiology images and reports. Interpreting this data at scale is essential for improving clinical care and accelerating clinical re…
Active label cleaning for improved dataset quality under resource constraints
Melanie Bernhardt, Daniel C. Castro, Ryutaro Tanno +9
Imperfections in data annotation, known as label noise, are detrimental to the training of machine learning models and have an often-overlooked confounding effect on the assessment…