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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Implementing Artificial Intelligence in Radiology: Design Thinking Road Map.

Vitor Ulisses Monnaka1, Jéssica Andrade-Silva1, Gilberto Szarf2

  • 1Department of Innovation, Hospital Israelita Albert Einstein, Avenida Albert Einstein, 627/701, São Paulo, 05652-900, Brazil, 55 1121511233.

JMIR AI
|April 29, 2026
PubMed
Summary
This summary is machine-generated.

Design thinking offers a roadmap for integrating artificial intelligence (AI) in radiology. This user-centered approach addresses challenges like performance and security for better clinical AI deployment.

Keywords:
artificial intelligenceclinical implementationdesign thinkinghuman-centered designradiologytechnology adoption

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Clinical Implementation

Background:

  • Artificial intelligence (AI) shows great promise for medical imaging but faces significant challenges in clinical practice.
  • Real-world AI integration is hindered by limited clinical impact, performance issues, security vulnerabilities, and regulatory hurdles.

Purpose of the Study:

  • To explore how design thinking principles can guide AI implementation in radiology.
  • To provide a structured approach for overcoming barriers to AI adoption in clinical settings.

Main Methods:

  • Applying design thinking principles: user-centeredness, multidisciplinary collaboration, and iterative refinement.
  • Focusing on identifying clinical needs, selecting validated AI solutions, and ensuring effective deployment.

Main Results:

  • Design thinking provides a practical framework for AI implementation in radiology.
  • This approach facilitates the identification of needs, validation of solutions, and continuous improvement.

Conclusions:

  • Design thinking offers a structured roadmap for successful AI integration in radiology.
  • Emphasizing user needs and collaboration is key to overcoming implementation challenges and ensuring effective AI deployment.