What Is Implementation Science: And Why It Matters for Bridging the Artificial Intelligence Innovation-to-Application Gap in Medical Imaging.
Authors
Affiliations (5)
Affiliations (5)
- School of Public Health, Tehran University of Medical Sciences, Tehran, Iran; Self-Care Academic Research Unit (SCARU), Department of Primary Care & Public Health, School of Public Health, Imperial College, London, UK. Electronic address: [email protected].
- Department of Biomedical Engineering, Washington University in St Louis, St Louis, MO, USA.
- Medical Education and Informatics, Sultan Qaboos University, Muscat, Sultanate of Oman; School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia.
- Mallinckrodt Institute of Radiology, Washington University, St Louis, MO, USA.
- Departments of Radiology and Physics, University of British Columbia, Vancouver, British Columbia, Canada.
Abstract
This article emphasizes the critical role of implementation science (IS) in translating artificial intelligence (AI) innovations in medical imaging into routine clinical practice. Despite rapid technological advances, a significant gap exists between AI development and real-world adoption due to organizational, behavioral, and infrastructural barriers. IS offers structured frameworks, models, and strategies-such as hybrid designs and human-centered approaches-to address these challenges. The article advocates for collaborative, stakeholder-driven co-creation, early stakeholder engagement, and multisectoral partnerships to ensure AI tools are useable, sustainable, and impactful. Integrating IS principles is essential to bridge the gap between innovation and clinical impact.