Using natural language processing to develop layperson summaries of clinical trials.

Project Details


The aim of the project is to develop a Machine Learning (ML) system to summarise clinical trials technical reports into lay summaries. This is timely because in January 2022 a new EU regulation will come into force requiring the sponsors of clinical trials to post a trial lay summary onto a new EU online portal. A key goal is to make healthcare information more accessible to the general population with a view to empowering them to make more informed health-related decisions.

The main technical innovation is the application of a combination of Natural Language Processing (NLP) text summarisation approaches to clinical trial reports. There are two main approaches of NLP-based text summarisation: extraction and abstraction. In extraction, the content from the corpus is consolidated into a summary, while in abstraction, the information from the corpus is transformed into new sentences. These initial algorithms have not been developed with technical clinical trials reports in mind, hence the will investigate a hybrid approach which involves a combination of extractive and abstractive summarisation. Specifically, as part of the project delivery the work will use Transformer based NLP methods within a text summarisation context.
StatusNot started

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 9 - Industry, Innovation, and Infrastructure


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.