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AI in Medical Education: A Grants Program to Advance Innovation in Medical Education is a grant from the Josiah Macy Jr. Foundation that funds demonstration projects exploring responsible, effective, and ethical use of artificial intelligence in medical education.
The program supports three demonstration projects, each receiving up to $200,000 over two years, focused on developing and testing AI-powered tools and methods that improve medical training outcomes. Example funded projects include AI-based surgical skill assessment using video analysis, AI-enhanced communication feedback systems for patient-physician interactions, and training frameworks for clinical-AI collaboration.
Eligible applicants are institutions involved in medical education, such as medical centers and schools of medicine. The current grant cycle has been awarded; check the Josiah Macy Jr. Foundation website for future opportunities.
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The Macy Foundation - Artificial Intelligence in Medical Education Artificial Intelligence in Medical Education Watch the Innovating Med Ed with AI: Insights from the Macy Report Webinar (Hosted by AAMC) Watch the AI in Med Ed Conference Recommendations Webinar (Hosted by AAMC) View AAMC's AI in Academic Medicine Webinar Series 2024 Conference on AI in Medical Education AI in Medical Education: A Grants Program to Advance Innovation in Medical Education As a follow-up to the 2024 Macy conference on AI in Medical Education , the Josiah Macy Jr. Foundation announced a special initiative to fund demonstration projects that advance our understanding of what responsible, effective, and ethical use of AI in medical education will look like in the immediate future.
AI in Medical Education: A Grants Program to Advance Innovation in Medical Education provides support for three demonstration projects, each receiving up to $200,000 over two years. Please see the descriptions of the awarded projects below . materials that emanated from the conference, please visit the Macy Conferences section of the website.
AI in Medical Education: A Grants Program to Advance Innovation in Medical Education Artificial Intelligence Driven Assessment of Resident Surgical Skill Using Video Analysis of Incision Closures in Open Surgery Beth Israel Deaconess Medical Center The grant will leverage computer vision and AI methods to provide automated assessments of surgical skill in open procedures for surgical residents.
Automated video analytics will be captured during incision closures from traditional room video and egocentric recording from smart glasses. The model’s outputs will then be available on a resident-facing web platform designed to support feedback and longitudinal skill tracking. The overall goal is to refine AI-based assessment for open procedures to augment feedback from educators and encourage targeted practice for surgical trainees.
PI: Gabriel Brat, MD, Assistant Professor of Surgery, Beth Israel Deaconess Medical Center, Assistant Professor of Biomedical Informatics, Harvard Medical School Communication Compass: AI-Enhanced Feedback System NYU Grossman School of Medicine Effective patient-physician communication is crucial for high-quality healthcare, but challenging to teach and assess consistently.
Traditional methods often lack the ability to provide timely, objective feedback, leading to gaps in learners' communication skills. To address this, we are developing Communication Compass, an AI-powered system designed to offer personalized, near real-time feedback on learners' communication skills by analyzing ambient audio from patient-physician interactions.
This system will use advanced AI to assess communication across various dimensions and provide structured, rigorously-validated feedback with real examples. We will test this system’s impact on both educational outcomes and patient care through a randomized trial.
Ultimately, Communication Compass aims to create an ethical, scalable framework for improving communication skills in medical education, benefiting learners and patients alike.
PIs: Yuliya Yoncheva, PhD, Research Assistant Professor, Institute for Innovations in Medical Education; Jesse Burk-Rafel, MD, MRes, Director of Research, Institute for Innovations in Medical Education Teaching Future Doctors to Team with AI: A Social Science Approach to Developing and Evaluating Training Methods for Clinical-AI Collaboration Across the ARiSE Network Stanford Center for Biomedical Informatics Research Large language models (LLMs) like ChatGPT are one of the fastest adopted medical technologies in history, now routinely appearing in both clinics and medical classrooms alike.
The stakes are high – multiple studies now show that high-performing artificial intelligence technologies don’t always improve doctor performance. In order to fully recognize the health benefits of these powerful AI systems, medical educators will need to figure out how to better train doctors to work with AI.
The ARiSE Research Network, based at Beth Israel Deaconess Medical Center / Harvard Medical School and Stanford University, will use gold standard social science methodologies to understand how doctors are currently using AI in their clinical care.
They will then run national randomized trials to determine which educational strategies truly boost doctor-AI teamwork in important clinical tasks like diagnosing illnesses, explaining care plans to patients and coordinating treatment. The curricula and assessments from this project will be released openly so medical schools and hospitals around the world can train future doctors to use AI confidently while keeping patients safe.
PIs: Jonathan H. Chen, MD, PhD, Assistant Professor & Director for Medical Education in Artificial Intelligence, Stanford Center for Biomedical Informatics Research; Adam Rodman, MD, MPH, FACP, Hospitalist, Beth Israel Deaconess Medical Center; Assistant Professor, Harvard Medical School Learn more about Our Grantees
Based on current listing details, eligibility includes: Institutions involved in medical education, such as medical centers and schools. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates Up to $200,000 over two years Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is rolling deadlines or periodic funding windows. Build your timeline backwards from this date to cover registrations, approvals, attachments, and final submission checks.
Federal grant success rates typically range from 10-30%, varying by agency and program. Build a strong proposal with clear objectives, measurable outcomes, and a well-justified budget to improve your chances.
Requirements vary by sponsor, but typically include a project narrative, budget justification, organizational capability statement, and key personnel CVs. Check the official notice for the complete list of required attachments.
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Small Shipyard Grant Program is a federal grant from the U.S. Department of Transportation's Maritime Administration (MARAD) that funds capital improvements and related upgrades to qualified small shipyard facilities to foster efficiency, competitive operations, and quality ship construction, repair, and reconfiguration. The program aims to strengthen the domestic shipbuilding and ship repair industry by supporting facilities that would otherwise lack resources for modernization. MARAD notes that applications far exceed available funds and only a small percentage of applicants are funded each year. Eligible applicants are the operating companies of small shipyards with a single facility and no more than 1,200 production employees. Approximately $8,750,000 was available for FY 2025. The FY 2025 deadline of May 15, 2025 has passed; applicants should monitor Grants.gov for the FY 2026 announcement.
Digital Humanities Advancement Grants is sponsored by National Endowment for the Humanities. The Digital Humanities Advancement Grants (DHAG) program supports innovative, experimental, and computationally challenging digital projects that enhance scholarly research, teaching, and public programming in the humanities. This includes work that contributes to critical infrastructure and emphasizes extensibility, reuse, replicability, and accessibility. Projects can be in any area of the humanities.