We focus on an exemplar study on linking routine neuroimaging assessments and electronic health records to identify the relationships between common physical and mental health conditions. Does the presence of post-stroke depression affect overall recovery? Can we discover more about this relationship by using machine learning techniques to ‘read’ medical notes which describe brain scan data? Using electronic health records, we will identify patients who have had a brain scan after their stroke. We will use natural language processing and supervised machine learning to convert their doctor's notes into structured (useable) data. So instead of having lots of words which describe the patient's signs and symptoms and their diagnosis, the computer will output a series of numbers in a table which ‘code’ for this data. We will then combine this structured brain scan data with clinical information about the patient’s mental health. With our research, we hope to identify patterns and links between what has been seen on a brain scan and whether or not someone develops depression. If we are successful, we hope that this technique could be used for many other conditions such as traumatic head injury, Alzheimer’s or Parkinson’s disease. Website https://mhdss.ac.uk/section/linking-electronic-health-data-identify-relationships-between-physical-and-mental-health Research team Heather Whalley, Toni-Kim Clarke, Beatrice Alex, Claire Grover, Andreas Grivas, William Whiteley Funder Medical Research Council (MRC grant MC_PC_17209) This article was published on 2024-09-24
