7th Global Gastroenterology and Artificial Intelligence Summit (Live)

7 -Kinsinger

Pdf Summary

This document presents an overview of the NIH’s efforts to advance artificial intelligence (AI) research in gastroenterology and biomedical sciences more broadly, focusing on empowering innovation through data-driven approaches and collaborative research. Chris Kinsinger, Ph.D., Assistant Director for Catalytic Data Resources at NIH, outlines the NIH mission to support bold, cross-disciplinary scientific programs that catalyze discovery and address high-priority biomedical challenges.<br /><br />A central theme is the NIH Common Fund's role in promoting “Bold Science” initiatives that generate FAIR (Findable, Accessible, Interoperable, Reusable), AI-ready biomedical data through ethical, multidisciplinary teams. Emphasis is placed on integrating AI into clinical workflows thoughtfully, acknowledging challenges such as AI-human collaboration. For example, studies like CheXpert indicate that AI assistance does not automatically improve diagnostic quality, underscoring the need to design AI systems for selective human-AI cooperation.<br /><br />The document references a framework of three waves of AI in biomedicine, progressing from service platforms to mature, practical applications and future bilingual integration of technical and clinical expertise expected by the early 2030s.<br /><br />NIH funding opportunities extend beyond the Common Fund, including institutes like NCI and NIDDK targeting informatics, digital health technologies, and AI/ML tools specifically for cancer and diabetes management.<br /><br />A highlighted Common Fund program, PRIMED-AI (Precision Medicine with AI: Integrating Imaging with Multimodal Data), aims to catalyze AI-based clinical decision support tools that integrate imaging with diverse clinical data to enable effective and sustainable precision medicine. PRIMED-AI supports interdisciplinary collaboration, best practices, and governance development. Funding announcements for PRIMED-AI initiatives will begin in Fall 2025, with multiple awards supporting logistics, validation, frameworks, partnerships, and clinical translation.<br /><br />Overall, the NIH is fostering AI innovation by supporting high-quality data generation, ethical AI development, and collaborative, translational approaches to improve biomedical research and healthcare delivery.

Keywords

NIH

artificial intelligence

gastroenterology

biomedical sciences

FAIR data

AI-human collaboration

PRIMED-AI

precision medicine

clinical decision support

multimodal data integration