I am a mixed-methods researcher and Physician Associate with a clinical background in emergency care and a specialist interest in ultrasound diagnostics. My PhD research explores the diagnostic accuracy and acceptability of AI-assisted point-of-care ultrasound (POCUS) for deep vein thrombosis diagnosis, with a particular focus on enabling non-specialist clinicians to perform diagnostic assessments outside traditional hospital settings. I previously completed an MSc in Vascular Ultrasound at Imperial College London, which inspired my interest in AI-assisted ultrasound technologies and improving diagnostic accessibility.
I also have a strong interest in the policy and ethical challenges surrounding AI in healthcare, particularly equitable access and global implementation. Alongside my PhD, I have been working with the Alan Turing Institute on projects exploring the broader impact of AI-technologies on healthcare systems.
This research investigates whether artificial intelligence can help non-specialist clinicians diagnose deep vein thrombosis using AI-guided handheld ultrasound devices. By enabling faster point-of-care diagnosis in GP surgeries, the project aims to reduce hospital referrals, improve accessibility for vulnerable patients, and help healthcare systems manage increasing clinical demand more efficiently.
This research investigated whether AI-guided handheld ultrasound can help diagnose deep vein thrombosis (DVT) in primary care. Through a systematic review, a clinical study involving 565 patients, and stakeholder interviews, the research found promising results but highlighted challenges involving image quality, accountability, and integration into NHS healthcare systems.