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A Framework for Applied AI in Healthcare
Tran Truong1,2, Paige Gilbank2, Kaleigh Johnson-Cover2
1Techna Institute, University Health Network, Toronto, Ontario, Canada.
Studies in Health Technology and Informatics
|August 24, 2019
Summary
Developing artificial intelligence in healthcare requires careful planning. A new framework addresses trust and transparency challenges for successful clinical implementation of AI technologies.
Area of Science:
- Health Informatics
- Artificial Intelligence in Medicine
- Technology Adoption
Background:
- Healthcare systems are slow to adopt new technologies.
- Artificial intelligence (AI) presents unique challenges in clinical settings, including trust and transparency.
- Early consideration of implementation is crucial for AI success.
Purpose of the Study:
- To create a framework for implementing artificial intelligence technologies in clinical settings.
- To address the specific challenges of trust and transparency in healthcare AI.
Main Methods:
- Development of a comprehensive implementation framework.
- Focus on early-stage integration and stakeholder engagement.
Main Results:
- A structured approach to facilitate AI adoption in healthcare.
- Guidelines to enhance trust and transparency in clinical AI.
Conclusions:
- The developed framework supports the integration of AI in healthcare.
- Addressing trust and transparency is key for effective AI implementation in clinical environments.
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