Health Equity

Health equity research focuses on identifying and mitigating disparities in healthcare access and outcomes across different populations, often driven by factors like race, gender, socioeconomic status, and geographic location. Current research emphasizes the use of machine learning models, including large language models (LLMs) and logistic regression, to analyze healthcare data and identify biases that perpetuate these inequities, with a particular focus on intersectional effects of multiple social determinants. This work is crucial for developing fairer and more effective healthcare systems, improving the accuracy and equity of AI-driven diagnostic and treatment tools, and ultimately reducing preventable health disparities globally.