Associate Professor / Associate Dean, Faculty Affairs and Accreditation (acting)
Faculty, Health Policy And Management
Health Policy and Management
Dr. Manaf Zargoush is an associate professor of Health Policy & Management at the DeGroote School of Business, McMaster University. He holds a Ph.D. in Healthcare Operations and Information Management (McGill University, Montreal, Canada), a Ph.D. in Decision Science and Statistics (ESSEC Business School, Paris, France), M.Phil. in Decision Sciences(ESSEC Business School, Paris, France), M.Sc. in Socio-Economic Systems Engineering (Sharif University of Technology, Tehran, Iran), and B.Sc. in Mechanical Engineering (Jundi-Shapoor University, Ahvaz, Iran). His main areas of research expertise and interests include using Data Science (machine learning, artificial intelligence, statistical modeling) for descriptive and predictive analytics and optimization (stochastic dynamic optimization, Markov and Semi-Markov Decision Processes, Partially Observable Markov Decision Processes) for prescriptive analytics of a wide range of health-related problems, such as medical decision-making, and healthcare operations management. His current main projects are chronic disease (particularly hypertension and diabetes) management and aging research (e.g., ALC in Canada and predicting the trajectory of disabilities among older adults). He is also interested in physicians' learning in uncertain environments as well as causal analytics using machine learning and big data.
Hrayer Aprahamian Vedat Verter Manaf Zargoush
Health Care Management Science
Mahsa madani Hosseini Saeed Beheshti Jafar Heydari Maryam Zangiabadi Manaf Zargoush
International Journal Of Disaster Risk Reduction
Mahsa madani Hosseini Manaf Zargoush Somayeh Ghazalbash
Health Promotion International
Alyaa Abdelhalim Manaf Zargoush Norman Archer Mehrdad Roham
Health Expectations
A Data-driven Analytical Model For Predicting Functional Loss And Recovery Among Older Adults
Mm Hosseini Manaf Zargoush F Alem
Proceedings Of The International Conference On Industrial Engineering And Operations Management
Identifying Predictors Of Covid-19 And Associated Risk Factors In Long-term Care And Retirement Homes Using Facility Administrative Data
Andrew Costa Manaf Zargoush Ahmad Von schlegell