3 citations · 9 across the 8 of their papers we have counts for
8 papers
LLM enhanced graph inference for long-term disease progression modelling
Tiantian He, An Zhao, Elinor Thompson +4
Understanding the interactions between biomarkers among brain regions during neurodegenerative disease is essential for unravelling the mechanisms underlying disease progression. F…
Connectomics Informed by Large Language Models
Elinor Thompson, Tiantian He, Anna Schroder +5
Tractography is a unique method for mapping white matter connections in the brain, but tractography algorithms suffer from an inherent trade-off between sensitivity and specificity…
DeCoRe: Decoding by Contrasting Retrieval Heads to Mitigate Hallucinations
Aryo Pradipta Gema, Chen Jin, Ahmed Abdulaal +5
Large Language Models (LLMs) often hallucinate, producing unfaithful or factually incorrect outputs by misrepresenting the provided context or incorrectly recalling internal knowle…
An X-Ray Is Worth 15 Features: Sparse Autoencoders for Interpretable Radiology Report Generation
Ahmed Abdulaal, Hugo Fry, Nina Montaña-Brown +5
Radiological services are experiencing unprecedented demand, leading to increased interest in automating radiology report generation. Existing Vision-Language Models (VLMs) suffer…
Disentangled Diffusion Autoencoder for Harmonization of Multi-site Neuroimaging Data
Ayodeji Ijishakin, Ana Lawry Aguila, Elizabeth Levitis +3
Combining neuroimaging datasets from multiple sites and scanners can help increase statistical power and thus provide greater insight into subtle neuroanatomical effects. However,…
Normative Diffusion Autoencoders: Application to Amyotrophic Lateral Sclerosis
Ayodeji Ijishakin, Adamos Hadjasavilou, Ahmed Abdulaal +7
Predicting survival in Amyotrophic Lateral Sclerosis (ALS) is a challenging task. Magnetic resonance imaging (MRI) data provide in vivo insight into brain health, but the low preva…
A coupled-mechanisms modelling framework for neurodegeneration
Tiantian He, Elinor Thompson, Anna Schroder +4
Computational models of neurodegeneration aim to emulate the evolving pattern of pathology in the brain during neurodegenerative disease, such as Alzheimer's disease. Previous stud…
Interpretable Alzheimer's Disease Classification Via a Contrastive Diffusion Autoencoder
Ayodeji Ijishakin, Ahmed Abdulaal, Adamos Hadjivasiliou +2
In visual object classification, humans often justify their choices by comparing objects to prototypical examples within that class. We may therefore increase the interpretability…