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Muhammad Mamdani

MPH, MA, PharmD

Scientist

Email: Muhammad.Mamdani@unityhealth.to
Tel: 416-864-3037

Research Programs

Biography

Dr. Mamdani is Vice President of Data Science and Advanced Analytics at Unity Health Toronto and Director of the University of Toronto Temerty Faculty of Medicine Centre for Artificial Intelligence Education and Research in Medicine (T-CAIREM). Dr. Mamdani’s team bridges advanced analytics including machine learning with clinical and management decision making to improve patient outcomes and hospital efficiency. Dr. Mamdani is also Professor in the Department of Medicine of the Temerty Faculty of Medicine, the Leslie Dan Faculty of Pharmacy, and the Institute of Health Policy, Management and Evaluation of the Dalla Lana Faculty of Public Health. He is also adjunct Senior Scientist at the Institute for Clinical Evaluative Sciences (ICES) and a Faculty Affiliate of the Vector Institute, which is a leading institution for artificial intelligence research in Canada.

Dr. Mamdani holds a Doctor of Pharmacy degree from the University of Michigan, a fellowship in pharmacoeconomics from the Detroit Medical Centre, a Master of Arts degree in econometric theory from Wayne State University, and a Master of Public Health from Harvard University with a focus on statistics and epidemiology. He has previously been named among Canada’s Top 40 under 40. Dr. Mamdani’s research interests include pharmacoepidemiology, pharmacoeconomics, drug policy, and the application of advanced analytics approaches to clinical problems and health policy decision-making. He has published over 500 studies in peer-reviewed healthcare journals.

Please note: Dr. Mamdani is not taking any summer students

Recent Publications

  1. Colacci, M, Pou-Prom, C, Siddiqi, A, Mamdani, M, Verma, AA. Evaluating sociodemographic bias in a deployed machine-learned patient deterioration model. JAMIA Open. 2025;8 (6):ooaf158. doi: 10.1093/jamiaopen/ooaf158. PubMed PMID:41334247 PubMed Central PMC12668680.
  2. Chang, SN, Exall, E, Dixon, C, Tickler, G, Mamdani, M, Body, R et al.. Beyond diagnostic test performance: two content-validated questionnaires assessing patient and clinician satisfaction with diagnostic tests. J Patient Rep Outcomes. 2025; :. doi: 10.1186/s41687-025-00964-4. PubMed PMID:41307602 .
  3. Mamdani, M. [Not Available]. CMAJ. 2025;197 (34):E1126-E1128. doi: 10.1503/cmaj.250888-f. PubMed PMID:41087044 PubMed Central PMC12527302.
  4. Li, B, Eisenberg, N, Beaton, D, Lee, DS, Al-Omran, L, Wijeysundera, DN et al.. Reply. J Vasc Surg. 2025;82 (4):1545-1547. doi: 10.1016/j.jvs.2025.06.037. PubMed PMID:40967721 .
  5. Fralick, M, Højbjerg Lassen, MC, Rangrej, J, Asgari, S, Rais, S, Hillmer, MP et al.. Predicting the occurrence of DKA following sodium glucose co-transporter-2 inhibitors: An international cohort study. J Diabetes Complications. 2025;39 (10):109144. doi: 10.1016/j.jdiacomp.2025.109144. PubMed PMID:40769111 .
  6. Ho, MKH, Santhireswaran, A, Gomes, T, Mamdani, M, Tadrous, M. Comparative effectiveness and safety of insulin reference biologics versus biosimilars for types 1 and 2 diabetes mellitus: Protocol for a systematic review of real-world studies. PLoS One. 2025;20 (7):e0329299. doi: 10.1371/journal.pone.0329299. PubMed PMID:40737300 PubMed Central PMC12310029.
  7. Khan, H, Zamzam, A, Shaikh, F, Mamdani, M, Saposnik, G, Qadura, M et al.. HE4 as a Prognostic Biomarker of Major Adverse Cardiovascular Events in Patients with Abdominal Aortic Aneurysm: A Canadian Prospective Observational Study. Biomedicines. 2025;13 (7):. doi: 10.3390/biomedicines13071562. PubMed PMID:40722638 PubMed Central PMC12292541.
  8. Mamdani, M. Canada's health innovation imperative. CMAJ. 2025;197 (26):E761-E762. doi: 10.1503/cmaj.250888. PubMed PMID:40721239 PubMed Central PMC12316693.
  9. Li, B, Aljabri, B, Beaton, D, Al-Omran, L, Hussain, MA, Lee, DS et al.. Predicting outcomes following endovascular aortoiliac revascularization using machine learning. NPJ Digit Med. 2025;8 (1):475. doi: 10.1038/s41746-025-01865-y. PubMed PMID:40707760 PubMed Central PMC12289885.
  10. Alanezi, T, Li, B, Al-Omran, L, Alshabanah, L, Alkhayal, NK, Verma, M et al.. Surgical Outcomes Through the Patient's Eyes: A Scoping Review of Patient-Reported Outcome Measures in Surgery. J Surg Res. 2025;313 :120-130. doi: 10.1016/j.jss.2025.06.039. PubMed PMID:40669370 .
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Affiliations & Other Activities

  • Scientist, Li Ka Shing Knowledge Institute, St. Michael’s Hospital
  • Professor, Institute of Health Policy, Management, and Evaluation, University of Toronto
  • Professor, Leslie Dan Faculty of Pharmacy, University of Toronto
  • Adjunct Professor, King Saud University Senior Adjunct
  • Scientist, Institute for Clinical Evaluative Sciences