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.
et al., 2019, Collaborative patterns, authorship practices and scientific success in biomedical research: a network analysis., J R Soc Med, Vol:112, Pages:245-257
et al., 2019, Anatomy 101 for AI-driven robotics: Explanatory, ethical and legal frameworks for development of cadaveric skills training standards in autonomous robotic surgery/autopsy., Int J Med Robot
Navaratne L, Ashrafian H, Martínez-Isla A, 2019, Quantifying tension in tension-free hiatal hernia repair: a new intra-operative technique., Surg Endosc
et al., Understanding health management and safety decisions using signal processing and machine learning., Bmc Medical Research Methodology, ISSN:1471-2288
et al., 2019, Bariatric surgery modulates urinary levels of microRNAs involved in the regulation of renal function, Frontiers in Endocrinology, Vol:10, ISSN:1664-2392