We're a community of 10,000+ Artificial Intelligence and Healthcare Experts
Lead, recruit, and coordinate the AIM-AHEAD Consortium
Assess, develop, and implement data science training curriculum
Assess data and computing infrastructure for AI/ML and health research
Address priorities and needs for AI/ML research with electronic health records
Explore the latest news, stories, and initiatives shaping the future of AI/ML healthcare innovation across our national network.
Dr. Huang, an Assistant Professor of University of Pennsylvania Perelman School of Medicine Pathology and Laboratory Medicine, will discuss the critical role of building an integrated ecosystem for medical imaging and demonstrate how AI can assist pathologists to enhance diagnostic accuracy and efficiency through multiple AI algorithm development efforts.
Find out more about how AIM-AHEAD CLINAQ Program participants Kalyani Narra (MD) and Dhruvangi Sharma (PhD) are advancing healthcare through AI/ML-driven research.
Register now to attend the coding session two, where Dr. Gordon Gao from Johns Hopkins University will explore practical, AI-assisted approaches to research, innovation, and problem-solving.
National Distribution of AI/ML Researchers on AIM-AHEAD Connect
We are a community of 10,230 researchers focused on leveraging AI/ML in biomedical research to improve healthcare, including 6,670 trainees, 2,330 experts, and 190 active discussion groups. AIM-AHEAD Connect is developed and maintained by the Communications Hub.
Connect with a vast network of mentors and mentees nationwide for advice and guidance.
Build your Mentoring network to further your career, upload your CV, search for members and their CVs and research interests.
Learn through free AI/ML courses designed for researchers, clinicians, and innovators. Explore the full course catalog and advance your skills today.
“Hallmarks of Success” are goals for the AIM-AHEAD Consortium to strive towards. These hallmarks have been aligned to AIM-AHEAD’s four North Stars, and is included in the AIM-AHEAD Coordinating Center (A-CC) evaluation plan. Cores, hubs, and consortium partners will report on how their activities contribute to which hallmark(s) to track progress.
Discover the national impact of our AIM-AHEAD Workforce Development Programs by exploring the map on the right. This map highlights the sixteen innovative initiatives and training collaborations that have been launched since 2022, including all program cohorts from Year 1 to Year 4. Visit our Programs page to learn more about how these AIM-AHEAD initiatives are shaping the future workforce in artificial intelligence, machine learning and healthcare by engaging hundreds of award recipients across the country.
Explore the national impact of our AIM-AHEAD Research Programs by viewing the map to the left. This map highlights the seven distinguished research initiatives launched since 2022, covering all program cohorts from Year 1 to Year 4. To learn more, visit our Programs page and see how these AIM-AHEAD programs are empowering researchers to leverage and enhance their capacity for artificial intelligence and machine learning, enabling them to conduct meaningful research nationwide.
Through the implementation of a two-phase funding model, PAIR has connected awardee institutions from across the United States with AIM-AHEAD resources, AI/ML and health experts, and grant-writing coaches to help establish AI/ML Health Research Labs which host cross-disciplinary teams for research projects and grant writing.
The Future of Artificial Intelligence and Mental Health is an asynchronous distinguished speaker series developed as part of the AIM-AHEAD Connect Course Series. The course brings together subject matter experts from across mental health, psychiatry, artificial intelligence, and related disciplines to explore both the opportunities and challenges associated with the growing role of AI in mental health.
Across four expert-led modules, participants will examine AI and mental health from multiple perspectives, including its implications for vulnerable populations and the relationship between AI and lived experiences of mental health and madness, the importance of trauma-informed AI, and the translation of AI and data-driven approaches into psychiatric research and practice.