4 papers
Fairness-Optimized Synthetic EHR Generation for Arbitrary Downstream Predictive Tasks
Mirza Farhan Bin Tarek, Raphael Poulain, Rahmatollah Beheshti
Among various aspects of ensuring the responsible design of AI tools for healthcare applications, addressing fairness concerns has been a key focus area. Specifically, given the wi…
Enabling Scalable Evaluation of Bias Patterns in Medical LLMs
Hamed Fayyaz, Raphael Poulain, Rahmatollah Beheshti
Large language models (LLMs) have shown impressive potential in helping with numerous medical challenges. Deploying LLMs in high-stakes applications such as medicine, however, brin…
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…