268 citations · 892 across the 24 of their papers we have counts for
7 papers · 1 filter
MAIRA-2: Grounded Radiology Report Generation
Shruthi Bannur, Kenza Bouzid, Daniel C. Castro +18
Radiology reporting is a complex task requiring detailed medical image understanding and precise language generation, for which generative multimodal models offer a promising solut…
MAIRA-1: A specialised large multimodal model for radiology report generation
Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid +12
We present a radiology-specific multimodal model for the task for generating radiological reports from chest X-rays (CXRs). Our work builds on the idea that large language model(s)…
Exploring the Boundaries of GPT-4 in Radiology
Qianchu Liu, Stephanie Hyland, Shruthi Bannur +16
The recent success of general-domain large language models (LLMs) has significantly changed the natural language processing paradigm towards a unified foundation model across domai…
Compositional Zero-Shot Domain Transfer with Text-to-Text Models
Fangyu Liu, Qianchu Liu, Shruthi Bannur +9
Label scarcity is a bottleneck for improving task performance in specialised domains. We propose a novel compositional transfer learning framework (DoT5 - domain compositional zero…
Neural Document Embeddings for Intensive Care Patient Mortality Prediction
Paulina Grnarova, Florian Schmidt, Stephanie L. Hyland +1
We present an automatic mortality prediction scheme based on the unstructured textual content of clinical notes. Proposing a convolutional document embedding approach, our empirica…
Knowledge Transfer with Medical Language Embeddings
Stephanie L. Hyland, Theofanis Karaletsos, Gunnar Rätsch
Identifying relationships between concepts is a key aspect of scientific knowledge synthesis. Finding these links often requires a researcher to laboriously search through scien- t…
A Generative Model of Words and Relationships from Multiple Sources
Stephanie L. Hyland, Theofanis Karaletsos, Gunnar Rätsch
Neural language models are a powerful tool to embed words into semantic vector spaces. However, learning such models generally relies on the availability of abundant and diverse tr…