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Implementing Artificial Intelligence in Radiology: A Design Thinking Roadmap
Vitor Ulisses Monnaka;
Jéssica Andrade-Silva;
Gilberto Szarf;
Henrique Min Ho Lee
ABSTRACT
Despite its promising potential to transform medical care, particularly in the field of medical image, the integration of artificial intelligence (AI) into clinical practice remains a complex and multifaceted challenge. In real-world settings, AI tools may demonstrate limited clinical impact, suboptimal performance, security vulnerabilities, and face regulatory constraints. This article explores how the principles of design thinking can provide a structured roadmap for AI implementation in radiology. By emphasizing user-centeredness, fostering multidisciplinary collaboration, and embedding iterative refinement, this approach offers practical guidance for identifying clinical and operational needs, selecting and validating appropriate solutions, and ensuring effective deployment with continuous improvement.
Citation
Please cite as:
Monnaka VU, Andrade-Silva J, Szarf G, Lee HMH
Implementing Artificial Intelligence in Radiology: Design Thinking Road Map