In September 2024, I completed an 8-month NIH-Sponsored training in Advanced Data Analysis with focus on addressing biases in artificial intelligence and machine learning for healthcare.
With access to over 8 million COVID-positive cases of de-identified patient data from the N3C Data Enclave, my team used supervised machine learning models to predict COVID-19 severity based on preexisting conditions of patients across different age, sex, & ethnicities. The N3C Data Enclave is the largest database in the US containing harmonized clinical data for COVID-19 research. At the end of the training, my team earned two separate awards for “Outstanding Oral Presentation” and “Teamwork Excellence”.
The primary objective of this initiative is to equip early-career researchers with the skills necessary to identify and address unmet needs related to potential biases and disparities within large datasets, as the field of artificial intelligence in medicine continues to advance.
The training plays an important role in supporting President Biden's Executive Order, specifically focusing on establishing regulatory standards for the responsible development and deployment of artificial intelligence in healthcare.
I’m grateful for the opportunity to contribute to advancing AI in healthcare and supporting efforts to address biases and disparities in clinical data.