Modelling and extracting disease progression from multiple patient documents

In mental health records, symptom progression information is often documented over time across patient documents, which can be particularly long and include variable terminology. For patients with a diagnosis of schizophrenia, extracting and combining this information is key to improved understanding of the condition’s course and treatment outcomes. The aim of this project is to develop a novel natural language processing (NLP) approach to model and extract symptom progression starting from multiple documents, with an initial focus on patients with a diagnosis of schizophrenia.