Hutan Ashrafian is a Clinical Lecturer in Surgery. His research objectives are to develop innovative and technological strategies to resolve the global healthcare burden of obesity, metabolic syndrome, obesity-related cardiorespiratory disease, musculoskeletal dysfunction and cancer.
His work encompasses clinical and mechanistic studies of metabolic bariatric surgery, complex biostatistical models, networks and evidence synthesis to guide policy decisions, computational physiology and systems medicine, novel health technology assessment and diagnostic accuracy of biomarkers, robotics and artificial intelligence agents in healthcare, ancient history analytics, academic impact & leadership metrics and regenerative strategies including sports-based and bio-inspired bionic therapies.
Navaratne L, Ashrafian H, Martínez-Isla A, 2019, Quantifying tension in tension-free hiatal hernia repair: a new intra-operative technique., Surg Endosc, Vol:33, Pages:3040-3049
et al., Threats to safe transitions from hospital to home: Consensus study in primary care, British Journal of General Practice, ISSN:0960-1643
et al., 2019, Understanding health management and safety decisions using signal processing and machine learning, Bmc Medical Research Methodology, Vol:19, ISSN:1471-2288
et al., 2019, Collaborative patterns, authorship practices and scientific success in biomedical research: a network analysis., Journal of the Royal Society of Medicine, Vol:112, ISSN:1758-1095, Pages:245-257
et al., 2019, Legal, regulatory and ethical frameworks or standards for AI and autonomous robotic surgery, WILEY, Pages:212-213, ISSN:1470-0328