2022
DOI: 10.3389/fdgth.2022.942588
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A Perspective on a Quality Management System for AI/ML-Based Clinical Decision Support in Hospital Care

Abstract: Although many artificial intelligence (AI) and machine learning (ML) based algorithms are being developed by researchers, only a small fraction has been implemented in clinical-decision support (CDS) systems for clinical care. Healthcare organizations experience significant barriers implementing AI/ML models for diagnostic, prognostic, and monitoring purposes. In this perspective, we delve into the numerous and diverse quality control measures and responsibilities that emerge when moving from AI/ML-model devel… Show more

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Cited by 10 publications
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“…A second practice was the importance of sound software and data-management principles, attributing accountability throughout the AI software's life cycle and encouraging a quality management approach to the AI system. 17 Finally, there was a common practice of continuous monitoring and auditing of the software. These align with the GMLP and identify similar themes in AI adoption.…”
Section: Current Best Practices In Ai Adoptionmentioning
confidence: 99%
“…A second practice was the importance of sound software and data-management principles, attributing accountability throughout the AI software's life cycle and encouraging a quality management approach to the AI system. 17 Finally, there was a common practice of continuous monitoring and auditing of the software. These align with the GMLP and identify similar themes in AI adoption.…”
Section: Current Best Practices In Ai Adoptionmentioning
confidence: 99%