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Bottom-up and top-down paradigms of artificial intelligence research approaches to healthcare data science using growing real-world big data.

Michelle WangMadhumita SushilBrenda Y MiaoAtul J Butte
Published in: Journal of the American Medical Informatics Association : JAMIA (2023)
This manuscript describes the diverse and growing AI research approaches in healthcare data science and categorizes them into 2 distinct paradigms, the bottom-up and top-down paradigms to provide health scientists venturing into artificial intelligent research with an understanding of the evolving computational methods and help in deciding on methods to pursue through the lens of real-world healthcare data.
Keyphrases
  • big data
  • artificial intelligence
  • healthcare
  • machine learning
  • deep learning
  • public health
  • electronic health record
  • mental health
  • health information
  • risk assessment
  • cataract surgery