معرفی
Nicholas Mills is the British Heart Foundation Professor of Cardiology at the University of Edinburgh, based in the Centre for Cardiovascular Science within the Deanery of Clinical Sciences. He serves as a Consultant Interventional Cardiologist at the Royal Infirmary of Edinburgh and leads the Data-Driven Innovation in Health and Social Care programme at the Usher Institute.
His academic credentials include a PhD in Cardiovascular Science (2009), MBChB in Medicine (2000), and BSc in Pharmacology (1998), all from the University of Edinburgh.
Professor Mills' research pioneers the use of linked Scottish healthcare data to develop and evaluate diagnostic tools for acute cardiac conditions. His work focuses on cardiac biomarkers like troponin, AI-driven decision support systems, and large-scale implementation studies to improve risk stratification and patient outcomes in real-world settings.
Analysis of his publication trends reveals a strategic evolution from foundational biomarker studies toward sophisticated AI applications and implementation science. Recent work emphasizes machine learning for myocardial infarction diagnosis and decision-support tools for acute heart failure, reflecting a shift toward data-driven clinical innovation.
His scientific distinctions include:
- Fellow of the Royal College of Physicians (FRCP)
- Fellow of the European Society of Cardiology (FESC)
- Fellow of the Academy of Medical Sciences (FMedSci)
He actively supervises PhD candidates and clinical fellows, including BHF-funded scholars and MRC research trainees. His group secures substantial funding from the British Heart Foundation, currently managing 81 projects (16 active) spanning cardiovascular risk prediction, AI diagnostics, and health inequality reduction. The team integrates clinical researchers, data scientists, and trial coordinators to translate findings into practice.
Housed within the Centre for Cardiovascular Science, his research environment features a multidisciplinary team of 15+ members including clinical leads, data managers, and research nurses, enabling end-to-end translation from data analysis to clinical implementation.
