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Updated: May 24, 2026

Non-radioactive in situ Hybridization Protocol Applicable for Norway Spruce and a Range of Plant Species

Non-radioactive in situ Hybridization Protocol Applicable for Norway Spruce and a Range of Plant Species

Published on: April 17, 2009

National Collaboration on AI Deployment in Norway.

Gro-Hilde Severinsen¹, Line Silsand¹

¹Norwegian center for e-health research.

Studies in Health Technology and Informatics

|May 23, 2026

Summary

This summary is machine-generated.

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Cost Containment
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Norway

Area of Science:

Health Informatics
Artificial Intelligence in Healthcare
Radiology AI Deployment

Background:

A national AI platform was implemented in Norway to standardize radiology AI procurement and deployment.
The platform aimed to facilitate coordinated scaling across all health regions.

Purpose of the Study:

To evaluate how the national AI platform approach enables and constrains AI deployment in Norwegian radiology.
To identify key themes influencing the adoption, scaling, and sustainability of AI.

Main Methods:

Formative process evaluation involving interviews with regional implementation leaders.
Analysis using the Non-Adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework.
Informed by information infrastructure (II) theory.

Keywords:

AI deployment formative process evaluation national platform radiology

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Non-radioactive in situ Hybridization Protocol Applicable for Norway Spruce and a Range of Plant Species

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Main Results:

The platform created a shared base, increasing access and competition but risking fragmentation.
It fostered interregional collaboration but revealed governance gaps hindering collective learning.
Increasing socio-technical complexity arose from multi-vendor platforms, validation, and integration.

Conclusions:

Norway's national AI platform is a promising but premature information infrastructure.
Stronger coordination is needed for scalable and sustainable AI deployment in radiology.