activity
20172023
most citedDLTK: State of the Art Reference Implementations for Deep Learning on Medical Images

74 citations · 307 across the 30 of their papers we have counts for

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Showing 2023Show all

9 papers · 1 filter

eess.IV20235 cited

Analysing race and sex bias in brain age prediction

Carolina Piçarra, Ben Glocker

Brain age prediction from MRI has become a popular imaging biomarker associated with a wide range of neuropathologies. The datasets used for training, however, are often skewed and…

eess.IV2023

Robustness Stress Testing in Medical Image Classification

Mobarakol Islam, Zeju Li, Ben Glocker

Deep neural networks have shown impressive performance for image-based disease detection. Performance is commonly evaluated through clinical validation on independent test sets to…

cs.CY2023

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah +117

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. I…

cs.CV2023

Distance Matters For Improving Performance Estimation Under Covariate Shift

Mélanie Roschewitz, Ben Glocker

Performance estimation under covariate shift is a crucial component of safe AI model deployment, especially for sensitive use-cases. Recently, several solutions were proposed to ta…

cs.LG2023

A Causal Ordering Prior for Unsupervised Representation Learning

Avinash Kori, Pedro Sanchez, Konstantinos Vilouras +2

Unsupervised representation learning with variational inference relies heavily on independence assumptions over latent variables. Causal representation learning (CRL), however, arg…

cs.CV2023

The Role of Subgroup Separability in Group-Fair Medical Image Classification

Charles Jones, Mélanie Roschewitz, Ben Glocker

We investigate performance disparities in deep classifiers. We find that the ability of classifiers to separate individuals into subgroups varies substantially across medical imagi…