François Grolleau, MD, MPH
Initially trained in clinical medicine, I hold full board certification (France) in Anesthesia and Critical Care. I shifted my attention to methodological research in medicine after completing a Master of Public Health from Université Paris Descartes and a fellowship at McMaster University (Canada).
I am currently an Assistant Professor of Biostatistics (Université Paris Cité), and a researcher at CRESS — METHODS team. My scientific work focuses on developing and implementing statistical/machine learning methods for the personalization of medical interventions. My applied areas of interest include Critical Care, Nephrology, and Cardiology.
For more information about my work, please visit my website at https://fcgrolleau.github.io/
Statistical reinforcement learning
F. Grolleau, R. Porcher, S. Barbar et al. Personalization of renal replacement therapy initiation: a secondary analysis of the AKIKI and IDEAL-ICU trials. Critical Care. 2022. [Paper]
F. Grolleau, GS. Collins, A. Smarandache et al. The fragility and reliability of conclusions of anesthesia and critical care randomized trials with statistically significant findings: A systematic review. Critical Care Medicine. 2019.