4 citations · 4 across the 4 of their papers we have counts for
5 papers
Anatomy-Grounded Weakly Supervised Prompt Tuning for Chest X-ray Latent Diffusion Models
Konstantinos Vilouras, Ilias Stogiannidis, Junyu Yan +2
Latent Diffusion Models have shown remarkable results in text-guided image synthesis in recent years. In the domain of natural (RGB) images, recent works have shown that such model…
Zero-Shot Medical Phrase Grounding with Off-the-shelf Diffusion Models
Konstantinos Vilouras, Pedro Sanchez, Alison Q. O'Neil +1
Localizing the exact pathological regions in a given medical scan is an important imaging problem that traditionally requires a large amount of bounding box ground truth annotation…
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…