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DOI 10.1148/radiol.253974

Медицинская библиотека · Radiology · 2026

Call to Action: Accelerating AI-driven Transformation in Medical Imaging and the Broader Health Care System.

Moy Linda, Vargas Alberto, Gichoya Judy Wawira, Lungren Matthew P, Martí-Bonmatí Luis, Hess Christopher P, Bredella Miriam A, Schnall Mitchell

СтатьяConsensus StatementОбзорПеревод в очереди

Аннотация

Global imaging demand now exceeds capacity due to an aging population, rising comorbidities, expanded indications for imaging, and workforce shortages. These pressures are reshaping national health care policy. At the same time, the competing demands to expand access to imaging services while reducing costs are creating momentum to reimagine imaging delivery through the integration of transformative technologies like artificial intelligence (AI). This consensus statement from the International Society for Strategic Studies in Radiology (IS3R) is a call to action, outlining promising AI solutions that increase workflow efficiency and align radiology with health system and payer priorities. Reflecting expert consensus from the IS3R meeting in Dublin, Ireland, in August 2025, this statement defines strategic directions for radiology amid accelerating digitalization, rapid innovation, and data-driven patient care. This article covers four domains: image interpretation, capacity building, data governance, and systemic digital transformation. This article examines how AI can address rising imaging demand and costs while addressing challenges related to improving data quality, standardization, and interoperability. It also highlights the need to re-engineer workflows and adapt to new care models while maintaining high-quality services. Finally, it presents consensus recommendations outlining how AI can enable multimodal health data integration and advance alignment with value-based care.

Для цитирования: Moy Linda, Vargas Alberto, Gichoya Judy Wawira, Lungren Matthew P, Martí-Bonmatí Luis, Hess Christopher P, Bredella Miriam A, Schnall Mitchell. Call to Action: Accelerating AI-driven Transformation in Medical Imaging and the Broader Health Care System.. Radiology. 2026. DOI: 10.1148/radiol.253974.

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