101 citations · 161 across the 22 of their papers we have counts for
6 papers · 1 filter
Toward Better Assessment of LLMs' Performance in Clinical Error Detection
Yifan Zhang, Rahmatollah Beheshti
Automated detection of errors in clinical documentation is a promising application of large language models (LLMs), yet decisions to deploy such models rest on benchmarks that eval…
AgenticSum: An Agentic Inference-Time Framework for Faithful Clinical Text Summarization
Fahmida Liza Piya, Rahmatollah Beheshti
Large language models (LLMs) offer substantial promise for automating clinical text summarization, yet maintaining factual consistency remains challenging due to the length, noise,…
ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs
Fahmida Liza Piya, Rahmatollah Beheshti
Unstructured clinical data can serve as a unique and rich source of information that can meaningfully inform clinical practice. Extracting the most pertinent context from such data…
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…