Joseph Cutteridge

I have a broad range of research experience spanning clinical, laboratory, and computational domains.

Previous projects include developing novel interventions to reduce surgical site infections, applying multimodal machine learning to automatically stratify patients with chronic venous disease, and conducting a large systematic review comparing participants in vascular surgery RCTs with the UK patient population to evaluate the generalisability of trial findings.

At the Nuffield Department of Surgical Sciences, I am working with Professor Regent Lee and Miss Kasia Bera, assisting with the pan-European VASCUL-AID study, which is aiming to develop trustworthy artificial intelligence tools to improve patient care in vascular surgery.

In addition, I am a teaching associate at Green Templeton College, delivering surgical bedside teaching to medical students in years 4 to 6, focusing on surgical history-taking and clinical examination skills.

I grew up in Hertfordshire, attending St Edmund’s College in Ware. I read medicine at Oxford, completing pre-clinical training at The Queen’s College, and clinical training at Green Templeton College. It was my vascular surgery rotation at the John Radcliffe that inspired me to become a vascular surgeon, where I worked alongside an exceptional team who provided much support, mentorship and encouragement.

I completed my academic foundation training in Yorkshire, during which I completed a PGCert in Health Research and Statistics, funded by Health Education England. My research placement was based at Hull Royal Infirmary, where I worked on developing novel methods to reduce the incidence of surgical site infection in vascular surgery.

I then chose to take time out of clinical training to complete a full-time MSc in Health Data Analytics and Machine Learning at Imperial College London. This was fully funded through the School of Public Health Master’s Scholarship, awarded to the single candidate who demonstrates the greatest leadership potential within their field. My thesis investigated the use of multimodal machine learning on venous duplex reports to automatically stratify patients with chronic venous disease by severity.

However, since graduating from Oxford, I have remained closely engaged with colleagues there, publishing several papers on the quality and validity of evidence in vascular surgery, and I am delighted to have returned to Oxford to continue this important work.