Healthc Inform Res.  2022 Jul;28(3):185-187. 10.4258/hir.2022.28.3.185.

Application Strategies for Artificial Intelligence– based Clinical Decision Support System: From the Simulation to the Real-World

Affiliations
  • 1Department of Nursing, Samsung Medical Center, Seoul, Korea
  • 2Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea
  • 3Digital Innovation Center, Samsung Medical Center, Seoul, Korea
  • 4Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea


Figure

  • Figure 1 Screenshots of a nursing AI-CDSS for pressure injury. The system is designed to predict patients at risk of developing a pressure injury, and it also provides a personalized interpretation of the components that contributed to the outcome. AI-CDSS: artificial intelligence clinical decision support system.

  • Figure 2 The process of applying an AI-CDSS to a real-world setting. The procedure demonstrates the distinction between algorithms utilized in practice. In each configuration, variables and algorithms are seen and selected differently. AI-CDSS: artificial intelligence clinical decision support system.


Reference

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