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This paper is in the following e-collection/theme issue:

Artificial Intelligence (2371) Machine Learning (2244) Decision Support for Health Professionals (1646) Applications of AI (346) Implementation Report (56) Clinical Information and Decision Making (2081) Design of Processes and Workflows (214)

Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/80342, first published .
Implementing an Artificial Intelligence Decision Support System in Radiology: Prospective Qualitative Evaluation Study Using the Nonadoption Abandonment Scale-Up, Spread, and Sustainability (NASSS) Framework

Implementing an Artificial Intelligence Decision Support System in Radiology: Prospective Qualitative Evaluation Study Using the Nonadoption Abandonment Scale-Up, Spread, and Sustainability (NASSS) Framework

Implementing an Artificial Intelligence Decision Support System in Radiology: Prospective Qualitative Evaluation Study Using the Nonadoption Abandonment Scale-Up, Spread, and Sustainability (NASSS) Framework

Authors of this article:

Sundresan Naicker1 Author Orcid Image ;   Paul Schmidt2 Author Orcid Image ;   Bruce Shar2 Author Orcid Image ;   Amina Tariq1 Author Orcid Image ;   Ashleigh Earnshaw1 Author Orcid Image ;   Steven McPhail1, 3 Author Orcid Image
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Journals

  1. Obilaja O, Okeke A, Nwosu-Ijiomah C, Ayeyemi B, Mensah A. Beyond Diagnostic Accuracy: Evaluating the Real-World Clinical Impact of AI-Enabled Radiology in Oncology and Nuclear Medicine. Oncology, Nuclear Medicine and Transplantology 2026;2(1):onmt016 View