Rate My Professor Iakovos Toumazis

Toumazis specializes in decision analytics for health, with a primary focus on cancer prevention and early detection modeling. His research includes developing personalized lung cancer screening strategies using decision-analytic models like the ENGAGE framework, evaluating the cost-effectiveness of cancer screening and prevention interventions, constructing natural history models for ovarian and lung cancers, and creating risk prediction models that account for non-smoking risk factors, race and ethnicity, comorbidities, and histology-specific risks. He has published over 50 peer-reviewed articles, abstracts, and conference papers, including "Risk Model-Based Lung Cancer Screening: A Cost-Effectiveness Analysis" in Annals of Internal Medicine (2023, PMID: 36745885) and "Cost-effectiveness Evaluation of the 2021 US Preventive Services Task Force Recommendation for Lung Cancer Screening" in JAMA Oncology (2021, PMID: 34673885). Since 2024, he has served as Co-Lead for Decision Analytics for Health in the Institute for Data Science in Oncology at MD Anderson. Toumazis contributes to numerous institutional committees, including the Lung Cancer Early Detection Working Group and Lung Cancer Screening Task Force since 2021, the Internal Advisory Board for the Shared Decision Making Core, and the MedTech Innovation Council. His honors include being a Finalist in the Lee B. Lusted Student Prize Competition at the Society for Medical Decision Making's 47th Annual Meeting (2025), Best Poster Award at Stanford's Integrative Biomedical Imaging Informatics Annual Retreat (2018), and Winner of the Society for Health Systems Best Graduate Student Paper Competition (2015).