TRUST-AI

Artificial intelligence is rapidly transforming healthcare, offering new opportunities to enhance clinical decision making, efficiency, and patient outcomes. However, ongoing concerns remain a barrier to widespread adoption. Current reporting guidelines provide valuable and detailed frameworks, but their focus on existing technologies limits their adaptability to emerging approaches. To address this gap, we propose TRUST-AI, a high-level guide designed by healthcare professionals for healthcare professionals. TRUST-AI distils seven domains: Transparency, Reliability, Use Case, Safety and Security, Treatment Equity, Affordability and Environmental Impact, and Integration. These are combined into an accessible guide to support the responsible evaluation of artificial intelligence systems in healthcare. The guide is intended to endure over time, maintaining its relevance as artificial intelligence technologies continue to advance and diversify. By embedding these principles, TRUST-AI seeks to equip healthcare professionals with the knowledge to act as informed gatekeepers, ensuring that trust in artificial intelligence can be established safely across evolving health sectors.

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Publication Details

Journal
Journal of Perioperative Practice
Published
2025-12-01
DOI
https://doi.org/10.1177/17504589251396483
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

TRUST-AI

Robert R. Crichton, Adam Julius, Remi Rothwell
Journal of Perioperative Practice
Artificial Intelligence in Healthcare and Education
article

TRUST-AI

Robert R. Crichton, Adam Julius, Remi Rothwell
article en

Abstract

Artificial intelligence is rapidly transforming healthcare, offering new opportunities to enhance clinical decision making, efficiency, and patient outcomes. However, ongoing concerns remain a barrier to widespread adoption. Current reporting guidelines provide valuable and detailed frameworks, but their focus on existing technologies limits their adaptability to emerging approaches. To address this gap, we propose TRUST-AI, a high-level guide designed by healthcare professionals for healthcare professionals. TRUST-AI distils seven domains: Transparency, Reliability, Use Case, Safety and Security, Treatment Equity, Affordability and Environmental Impact, and Integration. These are combined into an accessible guide to support the responsible evaluation of artificial intelligence systems in healthcare. The guide is intended to endure over time, maintaining its relevance as artificial intelligence technologies continue to advance and diversify. By embedding these principles, TRUST-AI seeks to equip healthcare professionals with the knowledge to act as informed gatekeepers, ensuring that trust in artificial intelligence can be established safely across evolving health sectors.

Journal of Perioperative PracticeVol. 36(1-2)
University College London (GB)
Openalex Percentile: Top 68%
Artificial Intelligence in Healthcare and Education
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TRUST-AI — Robert R. Crichton, Adam Julius, et al. · Journal of Perioperative Practice (2025) | TGRS Research Map | TGRS