Valentine Golden Ghanem, MSc, MPH, MLS (CORU)
Ghanaian Medical Scientist | Public Health Researcher | Epidemiologist
Principal Clinical Leadership & Community Health: Valentine Golden Ghanem is a Principal Medical Scientist with over a decade of clinical experience. He supervises high-volume diagnostic operations at the Cocoa Clinic, overseeing a workflow of more than 1,000 medical tests every day. His commitment to public health is anchored by extensive field experience, including the coordination of rural community health screenings for over 5,000 individuals, with a focus on the surveillance and control of malaria and hypertension.
Academic Excellence: He holds an M.Sc. in Data Science from the University of East London and an M.Sc. in Public Health from the University of Suffolk, both awarded with Distinction. He is currently advancing this interdisciplinary foundation by pursuing an LL.M. in International Law at Liverpool John Moores University to bridge the gap between epidemiology, computational analytics, and global health governance.
Technical Innovation: Valentine specializes in the synergy between laboratory medicine and clinical data science. He leverages machine learning, including XGBoost, Random Forest, and SHAP, alongside geospatial analysis tools such as LISA and QGIS to forecast infectious disease patterns and strengthen national health systems.
Professional Standing & Peer Review: He is dual-licensed as a registered Medical Scientist with the Allied Health Professions Council (Ghana) and CORU (Ireland). He is an active member of the Academy of Clinical Science and Laboratory Medicine (ACSLM) and the Ghana Association of Biomedical Laboratory Scientists (GABMLS). Beyond his clinical practice, he serves as an active Peer Reviewer for international medical journals, including the Cureus Journal of Medical Science.
Research Impact: As a published researcher, his work focuses on the spatial determinants of HIV/AIDS and health insurance inequities in Ghana. He is dedicated to translating complex diagnostic data into actionable, evidence-based models to promote global health equity and informed policy design.
