When you visit your doctor or attend hospital, information collected about you, including your symptoms, tests, investigations, diagnosis, and treatments, is entered on computers as electronic health records (EHRs). This information could help us learn how to tailor treatments more accurately for individual patients and to offer better and safer healthcare.

The Challenge

The challenge we face is that most of the information held within these records is in written form – sometimes referred to as unstructured text – which is difficult to use in research: for example, ‘the patient feels very tired and breathless, is losing weight, and says her heart is beating very fast’. We need to develop special computerised tools to process these words to ensure we have a full picture of all patient symptoms, experiences and diagnoses to use in research for patient benefit.

The Solution

We will establish a natural language processing (NLP) research community that will address the complexity of clinical text through development of shared tools and standards with inbuilt patient confidence and engagement, supporting joint working across industry, academia and the NHS. The community will be open and inclusive, and develop capability for UK-wide NLP research at scale whilst providing clear ‘quick-wins’ through exemplar projects, shared material and datasets for training and implementation, with the ultimate aim of integrating with other health data analytics. The project will lay the foundations for a sustainable model for collaborative working, thus attracting funding for next 4 years and beyond.

Team Members

Visiting Research Fellow; Post-Doctoral Data Scientist (Dec 2015 – Feb 2018)