Schizophrenia is a complex mental health condition that presents with a wide range of symptoms and outcomes. Moreover, the effectiveness of treatments for schizophrenia varies greatly among individuals. One of the primary challenges in understanding the factors that influence treatment response and outcomes is the lack of comprehensive clinical information beyond the diagnosis itself. However, exploiting advances in natural language processing (NLP) methods and techniques to extract medical information from free text clinical summaries, such as those available in electronic health record data, provides exciting opportunities to overcome this major limitation in mental health research.

This project will develop NLP methods to extract medical information related to treatment response, disease course and outcomes from clinical summaries created for research for people with schizophrenia. The NLP derived information will be validated through manually inspection of the clinical summaries, and also using recorded variables that are related to treatment, course and outcome in these samples. The NLP methods and techniques that emerge from this project will inform future research performed by the schizophrenia research group at Cardiff University.

This project will be co-supervised by a member of the School of Medicine.