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.

This 3MT® presentation describes how 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.

My research examines how OSCE (Objective Structured Clinical Examination) role-play simulations help prepare nurse-practitioner students for real-world primary care. Interviews with recent graduates show role plays build confidence, teach communication and clinical routines, and improve readiness for complex cases. Following best-practice guidelines enhances learning. Expanding these simulations could strengthen primary care, especially in underserved rural areas.