Application of Artificial Intelligence in the Health Care Safety Context: Opportunities and Challenges

Samer Ellahham, Nour Ellahham, Mecit Can Emre Simsekler

Research output: Contribution to journalArticlepeer-review

95 Scopus citations

Abstract

There is a growing awareness that artificial intelligence (AI) has been used in the analysis of complicated and big data to provide outputs without human input in various health care contexts, such as bioinformatics, genomics, and image analysis. Although this technology can provide opportunities in diagnosis and treatment processes, there still may be challenges and pitfalls related to various safety concerns. To shed light on such opportunities and challenges, this article reviews AI in health care along with its implication for safety. To provide safer technology through AI, this study shows that safe design, safety reserves, safe fail, and procedural safeguards are key strategies, whereas cost, risk, and uncertainty should be identified for all potential technical systems. It is also suggested that clear guidance and protocols should be identified and shared with all stakeholders to develop and adopt safer AI applications in the health care context.

Original languageBritish English
Pages (from-to)341-348
Number of pages8
JournalAmerican Journal of Medical Quality
Volume35
Issue number4
DOIs
StatePublished - 1 Jul 2020

Keywords

  • artificial intelligence
  • machine learning
  • patient safety
  • quality
  • safety

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