Transformer-based Multi-target Regression on Electronic Health Records for Primordial Prevention of Cardiovascular Disease. - Raphael Poulain; Mehak Gupta; Randi E. Foraker; Rahmatollah Beheshti (BIBM, 2021)

Flexible-Window Predictions on Electronic Health Records. - Mehak Gupta; Raphael Poulain; Thao-Ly T. Phan; H. Timothy Bunnell; Rahmatollah Beheshti (AAAI, 2022)

An Extensive Data Processing Pipeline for MIMIC-IV. - Mehak Gupta; Brennan Gallamoza; Nicolas Cutrona; Pranjal Dhakal; Raphael Poulain; Rahmatollah Beheshti (ML4H@NeurIPS, 2022)

Few-Shot Learning with Semi-Supervised Transformers for Electronic Health Records. - Raphael Poulain; Mehak Gupta; Rahmatollah Beheshti (MLHC, 2022)

Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods. - Raphael Poulain; Mirza Farhan Bin Tarek; Rahmatollah Beheshti (FAccT, 2023)

Graph Transformers on EHRs: Better Representation Improves Downstream Performance. - Raphael Poulain; Rahmatollah Beheshti (ICLR, 2024)

Bias patterns in the application of LLMs for clinical decision support: A comprehensive study. - Raphael Poulain; Hamed Fayyaz; Rahmatollah Beheshti (CoRR, 2024)

Fairness-Optimized Synthetic EHR Generation for Arbitrary Downstream Predictive Tasks. - Mirza Farhan Bin Tarek; Raphael Poulain; Rahmatollah Beheshti (CoRR, 2024)

Aligning (Medical) LLMs for (Counterfactual) Fairness. - Raphael Poulain; Hamed Fayyaz; Rahmatollah Beheshti (CoRR, 2024)

Enabling Scalable Evaluation of Bias Patterns in Medical LLMs. - Hamed Fayyaz; Raphael Poulain; Rahmatollah Beheshti (CoRR, 2024)