After graduating in Computer Science from Durham University in 2019, I stayed on in Durham to pursue a PhD in machine learning for healthcare. My research focuses on explainable machine learning, particularly on how cutting-edge research can be applied to the healthcare domain to improve the clinical use and trustworthiness of machine learning models. This has led to research consisting of two intertwined strands: the theoretical development of novel ML techniques that improve the explainability and robustness of ML models, and the application of these models in healthcare.
My work has been published in venues such as ICPR, WACV and Nature Scientific Reports, with my research being the recipient of numerous awards such as the WACV 2022 Best Paper Award and 2023 Best Poster Award from the Society of Acute Medicine. After graduating from my PhD in 2023, I was part of a team successful in securing a large Innovate UK grant to study the use of machine learning to predict renal and hepatic dysfunction in chemotherapy patients. I led the machine learning aspect of this work and, in collaboration with Evergreen Life and UCLH, successfully deployed the developed models into clinics throughout the UK for use in prospective studies.
I was also part of a successful grant application to investigate winter pressures within the NHS, funded by HDR UK and NIHR. Working as a team on using machine learning to analyse electronic health records, I spearheaded the use of large language models to incorporate freetext triage notes into our modelling. This work has been presented to the Department of Health and Social Care as part of a policy briefing on addressing winter pressures in the NHS. A significant part of my work is conveying complex machine learning techniques to clinicians and other non-computer science audiences, and have presented at numerous cross-disciplinary venues such as the HDR UK Conference 2024 and the International Conference of the Society of Acute Medicine. I am also a committee member of the British Oncology Pharmacy Association’s AI Special Interest Group, working to educate Oncology Pharmacists about the role artificial intelligence and machine learning can play in their work.
The success of such interdisciplinary work is a product of your collaborators, and I work closely with clinical partners at UCL, Northern Care Alliance, University of Manchester and University of Bolton. I have also been at the forefront of new collaborations between Durham University and County Durham and Darlington NHS Foundation Trust, working on creating new research projects between the Department of Computer Science and medical experts at the hospital.