projects

The Equitable AI in Healthcare (EQUAIH) Lab is dedicated to advancing equitable AI in healthcare, tackling algorithmic bias, and addressing social determinants of health to improve patient care. Our research spans clinical decision support, healthcare disparities, and the development of fair and inclusive AI models.

work

Social Determinants of Health in ICUs

Investigating how social factors influence patient outcomes in intensive care settings, integrating this data into AI models to enhance predictions and interventions.

Management of Stroke and Shock

Studying patients on treatments to better understand demographic impacts and clinical outcomes, aiming to refine critical care strategies.

Open Access Clinical Reports and SDOH Databases

Creating a comprehensive open-access database that combines ICU reports with social determinants data, enhancing AI-driven clinical decision-making and understanding of non-clinical factors in critical care.

Bias in Medical Interventions and Devices

Investigating biases in medical devices and interventions to promote fairer, more effective healthcare technologies.

Phenotypic Study of Subarachnoid Hemorrhage Patients

Conducting detailed analyses of phenotypic data from experimental subarachnoid hemorrhage cases to improve diagnostic and treatment protocols.

Predicting Outcomes in Intensive Care

Using AI to forecast clinical outcomes and treatment responses in patients with conditions, enhancing personalized care strategies.