7 citations · 9 across the 4 of their papers we have counts for
4 papers
Aligning (Medical) LLMs for (Counterfactual) Fairness
Raphael Poulain, Hamed Fayyaz, Rahmatollah Beheshti
Large Language Models (LLMs) have emerged as promising solutions for a variety of medical and clinical decision support applications. However, LLMs are often subject to different t…
Bias patterns in the application of LLMs for clinical decision support: A comprehensive study
Raphael Poulain, Hamed Fayyaz, Rahmatollah Beheshti
Large Language Models (LLMs) have emerged as powerful candidates to inform clinical decision-making processes. While these models play an increasingly prominent role in shaping the…
HealthGAT: Node Classifications in Electronic Health Records using Graph Attention Networks
Fahmida Liza Piya, Mehak Gupta, Rahmatollah Beheshti
While electronic health records (EHRs) are widely used across various applications in healthcare, most applications use the EHRs in their raw (tabular) format. Relying on raw or si…
Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods
Raphael Poulain, Mirza Farhan Bin Tarek, Rahmatollah Beheshti
Developing AI tools that preserve fairness is of critical importance, specifically in high-stakes applications such as those in healthcare. However, health AI models' overall predi…