55 citations · 287 across the 28 of their papers we have counts for
29 papers
Large Language Models Perform on Par with Experts Identifying Mental Health Factors in Adolescent Online Forums
Isabelle Lorge, Dan W. Joyce, Andrey Kormilitzin
Mental health in children and adolescents has been steadily deteriorating over the past few years. The recent advent of Large Language Models (LLMs) offers much hope for cost and t…
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…
Clinical Prompt Learning with Frozen Language Models
Niall Taylor, Yi Zhang, Dan Joyce +2
Prompt learning is a new paradigm in the Natural Language Processing (NLP) field which has shown impressive performance on a number of natural language tasks with common benchmarki…