Pirracchio, Romain

Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare

Feng, J., Phillips, R. V., Malenica, I., Bishara, A., Hubbard, A. E., Celi, L. A., & Pirracchio, R. (2022) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 423

Mortality prediction in intensive care units with the Super ICU Learner Algorithm (SICULA): a population-based study.

Pirracchio, R., Petersen, M. L., Carone, M., Rigon, M. R., Chevret, S., & van der Laan, M. J. (2015) · The Lancet Respiratory Medicine

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 374

Improving propensity score estimators’ robustness to model misspecification using super learner.

Pirracchio, R., Petersen, M. L., & van der Laan, M. (2015) · American Journal of Epidemiology

Advanced Causal Inference TechniquesStatistical Methods in Clinical Trials

Cited by 186

Not All Clinical AI Monitoring Systems Are Created Equal: Review and Recommendations

Feng, J., Xia, F., Singh, K., & Pirracchio, R. (2025) · NEJM AI

Healthcare Technology and Patient MonitoringArtificial Intelligence in Healthcare and Education

Cited by 28

Harnessing AI in critical care: opportunities, challenges and key steps for success

Kalimouttou, A., Stevens, R. D., & Pirracchio, R. (2026) · Thorax

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 12