معرفی
Kazem Rahimi is a Professor of Cardiovascular Medicine and Population Health at the University of Oxford and a consultant cardiologist at the Oxford University Hospitals NHS Trust. He holds leadership positions as Chair of the Research Working Group and member of the Senior Executive Group at the Nuffield Department of Women's and Reproductive Health, where he also leads the Data Science Theme.
His research focuses on hypertension, heart failure, valvular heart disease and preventive cardiovascular medicine using methodologies including individual-patient meta-analysis, large-scale decentralized clinical trials, and digital health technologies. He leads the Deep Medicine programme with emphasis on machine learning applications to electronic health records and heads the Blood Pressure Lowering Treatment Trialists' Collaboration (BPLTTC), an international collaboration of major blood pressure lowering drug trials.
His recent publications demonstrate expertise across cardiovascular guidelines development, meta-analyses of maternal health impacts on congenital conditions, cardio-oncology intersections, hypertension management, and AI-driven risk prediction models for cardiovascular disease prevention. These works span clinical cardiology, epidemiological research, and innovative applications of artificial intelligence in medicine.
- Editor-in-Chief of BMJ Heart
- Deputy Chair of NIHR Academy Panel, Doctoral Fellowship Scheme
- Panel College Member of UKRI Future Leaders Fellowship scheme
- Advisory Board Member for Medtronic PLC Renal Denervation Programme
- Member of European Society of Cardiology Guidelines Methodology Group
- Former member of NICE Medical Technology Advisory Committee (until 2024)
- Former Specialty Editor of PLOS Medicine (until 2022)
- Advisor to World Health Organisation
- Co-founder of Zeesta Ltd (www.zeesta.ai)
Professor Rahimi's advisory and grant activities reflect his leadership in cardiovascular research methodology, clinical trial design, and translation of research into clinical practice guidelines. His work bridges academic medicine, clinical practice, and health technology development through collaborations with international organizations, pharmaceutical companies, and research institutions. His Deep Medicine programme represents a significant investment in applying advanced computational approaches to cardiovascular population health.
He leads research teams focused on cardiovascular epidemiology, clinical trials methodology, and digital health innovation, with particular emphasis on hypertension management and cardiovascular risk prediction using large-scale health data resources.
