Program Directors

Co-Directors: Usha Sambamoorthi, PhD, Damaris Javier, PhD, Jamboor K. Vishwanatha, PhD

MPIs: Bettina Beech, PhD, Evelinn Borrayo, PhD, Alejandra Casillas, PhD, Anil Shanker, PhD

Purpose

The purpose of the AIM-AHEAD ScHARe Equity in Population Health AI: Beyond EHR training program is to support institutions in building AI/ML infrastructure and to ensure FISMA compliance, enabling them to meet program goals effectively. This includes enhancing the security and data management practices necessary for handling sensitive information. By providing resources and guidance, the program aims to foster a more robust, compliant AI/ML environment that aligns with national standards.

About AIM-AHEAD

Artificial Intelligence/Machine Learning Consortium to Advance Health Equity And Researcher Diversity (AIM-AHEAD) is an initiative funded by the National Institutes of Health that is dedicated to enhancing diversity in the field of artificial intelligence and machine learning (AI/ML), with emphasis on reducing health disparities and promoting health equity. Led by the AIM-AHEAD Coordinating Center, this initiative has cultivated a diverse nationwide consortium that embraces equity and transparency, aimed at leveraging AI/ML to enhance health outcomes across diverse and under-resourced communities. Through the establishment of strategic partnerships, targeted research programs, and engagement with key stakeholders, AIM-AHEAD continues to bolster participation and foster meaningful involvement within the AI/ML and health equity field.

Participants

To accomplish this objective, a cohort of up to 25 diverse professionals committed to utilizing AI for population health research will complete an 8-month training program that will equip trainees with the health equity research and skills to navigate the unique challenges associated with applying AI, including Machine Learning (ML), to population health datasets that are collected using complex sample designs such as clustering, stratification, and weighting. Recognizing the growing emphasis on community engagement in AI/ML, the training program will include training in community engaged science methods that will secure user input from data set selection to implementation.

Impact

The AIM-AHEAD ScHARE program aims to expand AI/ML resources and build capacity for data-sharing in underrepresented institutions. This initiative fosters collaborations and enhances data infrastructure to support equitable health research. The expected impact includes stronger partnerships, improved data accessibility, and more inclusive health outcomes.

Program Inquiries

All questions and inquiries regarding this program can be directed to the AIM-AHEAD Training Programs HelpDesk. Please create a help ticket here: HelpDesk - Submit a Ticket