Romain Pirracchio

According to our database, Romain Pirracchio authored at least 14 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A deep learning approach for generating intracranial pressure waveforms from extracranial signals routinely measured in the intensive care unit.

Shiker S. Nair, Alina Guo, Joseph Boen, Ataes Aggarwal, Ojas Chahal, Arushi Tandon, Meer Patel, Sreenidhi Sankararaman, Nicholas J. Durr, Tej D. Azad, Romain Pirracchio, Robert D. Stevens

Comput. Biol. Medicine, 2024

Designing monitoring strategies for deployed machine learning algorithms: navigating performativity through a causal lens.

Jean Feng, Adarsh Subbaswamy, Alexej Gossmann, Harvineet Singh, Berkman Sahiner, Mi-Ok Kim, Gene Anthony Pennello, Nicholas Petrick, Romain Pirracchio, Fan Xia

Proceedings of the Causal Learning and Reasoning, 2024

Monitoring machine learning-based risk prediction algorithms in the presence of performativity.

Jean Feng, Alexej Gossmann, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Is this model reliable for everyone? Testing for strong calibration.

Jean Feng, Alexej Gossmann, Romain Pirracchio, Nicholas Petrick, Gene Pennello, Berkman Sahiner

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

A Brief Tutorial on Sample Size Calculations for Fairness Audits.

Harvineet Singh, Fan Xia, Mi-Ok Kim, Romain Pirracchio, Rumi Chunara, Jean Feng

CoRR, 2023

Towards a Post-Market Monitoring Framework for Machine Learning-based Medical Devices: A case study.

Jean Feng, Adarsh Subbaswamy, Alexej Gossmann, Harvineet Singh, Berkman Sahiner, Mi-Ok Kim, Gene Pennello, Nicholas Petrick, Romain Pirracchio, Fan Xia

CoRR, 2023

Multi-task Highly Adaptive Lasso.

Ivana Malenica, Rachael V. Phillips, Daniel Lazzareschi, Jeremy R. Coyle, Romain Pirracchio, Mark J. van der Laan

CoRR, 2023

2022

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

Jean Feng, Rachael V. Phillips, Ivana Malenica, Andrew Bishara, Alan E. Hubbard, Leo A. Celi, Romain Pirracchio

npj Digit. Medicine, 2022

Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees.

Jean Feng, Alexej Gossmann, Berkman Sahiner, Romain Pirracchio

J. Am. Medical Informatics Assoc., 2022

Monitoring machine learning (ML)-based risk prediction algorithms in the presence of confounding medical interventions.

Jean Feng, Alexej Gossmann, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio

CoRR, 2022

Sequential algorithmic modification with test data reuse.

Jean Feng, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio, Alexej Gossmann

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Personalized Online Machine Learning.

Ivana Malenica, Rachael V. Phillips, Romain Pirracchio, Antoine Chambaz, Alan E. Hubbard, Mark J. van der Laan

CoRR, 2021

The Physiological Deep Learner: First application of multitask deep learning to predict hypotension in critically ill patients.

Ményssa Cherifa, Yannet Interian, Alice Blet, Matthieu Resche-Rigon, Romain Pirracchio

Artif. Intell. Medicine, 2021

2019

Expert-Augmented Machine Learning.

Efstathios D. Gennatas, Jerome H. Friedman, Lyle H. Ungar, Romain Pirracchio, Eric Eaton, L. Reichman, Yannet Interian, Charles B. Simone II, A. Auerbach, E. Delgado, Mark J. van der Laan, Timothy D. Solberg, Gilmer Valdes

CoRR, 2019