Enhancing Fairness and Trustworthiness in Healthcare Language Models

Abstract

The rapid adoption of language models in healthcare has opened new opportunities for improving patient care, knowledge dissemination, and decision-making. However, these models are often undermined by systemic biases embedded in their outputs, posing risks to fairness, reliability, and trustworthiness in sensitive healthcare applications.