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Leveraging artificial intelligence to advance implementation science: potential opportunities and cautions.

Katy E TrinkleyRuopeng AnAnna M MawRussell E GlasgowRoss C Brownson
Published in: Implementation science : IS (2024)
Artificial intelligence holds promise to advance implementation science methods ("why") and accelerate its goals of closing the evidence-to-practice gap ("purpose"). However, evaluation of artificial intelligence's potential unintended consequences must be considered and proactively monitored. Given the technical nature of artificial intelligence applications as well as their potential impact on the field, transdisciplinary collaboration is needed and may suggest the need for a subset of implementation scientists cross-trained in both fields to ensure artificial intelligence is used optimally and ethically.
Keyphrases
  • artificial intelligence
  • big data
  • machine learning
  • primary care
  • deep learning
  • healthcare
  • quality improvement
  • public health
  • global health