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What Is Implementation Science: And Why It Matters for Bridging the Artificial Intelligence Innovation-to-Application
Ahmad Fayaz-Bakhsh1, Janice Tania2, Syaheerah Lebai Lutfi3
1School 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.
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.
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