Fellowship Bio

James is an emergency physician and part of the first cohort of Clinical AI Fellows. He has an interest in leveraging data to aid clinical decision making and risk stratification in emergency care.

Fellowship Project

Novel predictive algorithm development for high-cost early mental health care

South London and Maudsley NHS Foundation Trust

The goal of the project was to develop a predictive model for high intensity users in mental health care, based on the first three months of data extracted from an anonymised data pipeline. Dr Lai developed an algorithm to predict high- intensity users of mental health care using data held in electronic health records (EHR) at the South London and Maudsley NHS Trust. The aim was to develop a working model to classify patients as predicted ‘high- intensity’ users at 12 months’ after initial assessment. Dr Lai also worked with the team from the Centre for Translational Informatics to extract anonymised data from the Clinical Record Interactive Search (CRIS) system within the NIHR Maudsley Biomedical Research Centre

Fellowship Testimonial

This fellowship has given me the breadth of knowledge to become a member of the Royal College of Emergency Medicine Best Practice Committee, where I hope to develop guidance on the adoption of AI and digital technologies in emergency care. I will also be starting a PhD involving Machine Learning with the Major Trauma Service at Imperial College London and St Mary’s Hospital.