Rate My Professor Nophar Geifman

Geifman's research centres on data sciences in healthcare and medicine, utilizing artificial intelligence, big-data analytics, and machine learning to enhance patient stratification, biomarker discovery from diverse clinical and 'omics' datasets, and patient-centric predictions, treatments, and outcomes. She emphasizes open sharing of biomedical data and addresses oversimplifications in conventional disease research. Key publications encompass 'Quantifying new threats to health and biomedical literature integrity from rapidly scaled publications and problematic research' (2026, Journal of Clinical Epidemiology, co-authored with Matt Spick et al.), 'Safeguarding Open Science from exploitative practices' (2025, PLoS Medicine, with Daniel Maupin and Matt Spick), 'A plasma-based protein signature association with all-cause mortality' (2025, PLoS ONE, with Natalia Koziar and Anthony D. Whetton), 'Integrating Food Preference Profiling, Behavior Change Strategies, and Machine Learning for Cardiovascular Disease Prevention in a Personalized Nutrition Digital Health Intervention' (2025, Journal of Medical Internet Research, with Hana Fitria Navratilova and Anthony David Whetton), and 'An Interpretable Model for Predicting Acute Myocardial Infarction in Distinct Patient Profiles' (2025, Proceedings of MIE, with Anthony Onoja et al.). Listed on Google Scholar with over 2,200 citations, her contributions advance biomedical informatics, precision medicine, biomarkers, and AI applications in medicine. At the University of Surrey, she plays a pivotal role in establishing health and biomedical informatics as a centre of excellence.