2 citations · 4 across the 5 of their papers we have counts for
5 papers
Developing Healthcare Language Model Embedding Spaces
Niall Taylor, Dan Schofield, Andrey Kormilitzin +2
Pre-trained Large Language Models (LLMs) often struggle on out-of-domain datasets like healthcare focused text. We explore specialized pre-training to adapt smaller LLMs to differe…
Bespoke Large Language Models for Digital Triage Assistance in Mental Health Care
Niall Taylor, Andrey Kormilitzin, Isabelle Lorge +2
Contemporary large language models (LLMs) may have utility for processing unstructured, narrative free-text clinical data contained in electronic health records (EHRs) -- a particu…
Efficiency at Scale: Investigating the Performance of Diminutive Language Models in Clinical Tasks
Niall Taylor, Upamanyu Ghose, Omid Rohanian +4
The entry of large language models (LLMs) into research and commercial spaces has led to a trend of ever-larger models, with initial promises of generalisability, followed by a wid…
Detecting the Clinical Features of Difficult-to-Treat Depression using Synthetic Data from Large Language Models
Isabelle Lorge, Dan W. Joyce, Niall Taylor +3
Difficult-to-treat depression (DTD) has been proposed as a broader and more clinically comprehensive perspective on a person's depressive disorder where despite treatment, they con…
Personalised recommendations of sleep behaviour with neural networks using sleep diaries captured in Sleepio
Alejo Nevado-Holgado, Colin Espie, Maria Liakata +6
SleepioTM is a digital mobile phone and web platform that uses techniques from cognitive behavioural therapy (CBT) to improve sleep in people with sleep difficulty. As part of this…