Adapting and validating a Natural Language Processing tool developed for extracting data on perinatal self-harm, for use in other clinical populations in CRIS
Self-harm is common in both adults and children and good quality data on regarding self-harm is required to conduct research informing prevention, early identification and management. A Natural Language Processing (NLP) tool has been developed to extract data on self-harm from free-text in CRIS for a pregnant and postnatal population of patients. The purpose of this project is to adapt and test the existing tool with the aim of using it for other populations including children and young people.