5 citations · 15 across the 8 of their papers we have counts for
8 papers
Automated clinical coding using off-the-shelf large language models
Joseph S. Boyle, Antanas Kascenas, Pat Lok +2
The task of assigning diagnostic ICD codes to patient hospital admissions is typically performed by expert human coders. Efforts towards automated ICD coding are dominated by super…
Group Distributionally Robust Knowledge Distillation
Konstantinos Vilouras, Xiao Liu, Pedro Sanchez +2
Knowledge distillation enables fast and effective transfer of features learned from a bigger model to a smaller one. However, distillation objectives are susceptible to sub-populat…
Compositional Representation Learning for Brain Tumour Segmentation
Xiao Liu, Antanas Kascenas, Hannah Watson +2
For brain tumour segmentation, deep learning models can achieve human expert-level performance given a large amount of data and pixel-level annotations. However, the expensive exer…
Finding-Aware Anatomical Tokens for Chest X-Ray Automated Reporting
Francesco Dalla Serra, Chaoyang Wang, Fani Deligianni +2
The task of radiology reporting comprises describing and interpreting the medical findings in radiographic images, including description of their location and appearance. Automated…
The role of noise in denoising models for anomaly detection in medical images
Antanas Kascenas, Pedro Sanchez, Patrick Schrempf +9
Pathological brain lesions exhibit diverse appearance in brain images, in terms of intensity, texture, shape, size, and location. Comprehensive sets of data and annotations are dif…
HSIC-InfoGAN: Learning Unsupervised Disentangled Representations by Maximising Approximated Mutual Information
Xiao Liu, Spyridon Thermos, Pedro Sanchez +2
Learning disentangled representations requires either supervision or the introduction of specific model designs and learning constraints as biases. InfoGAN is a popular disentangle…