Artificial Intelligence for Rapid Meta-Analysis: Case Study on Ocular Toxicity of Hydroxychloroquine.

Journal: Journal of medical Internet research
PMID: 32804086

Abstract

BACKGROUND: Rapid access to evidence is crucial in times of an evolving clinical crisis. To that end, we propose a novel approach to answer clinical queries, termed rapid meta-analysis (RMA). Unlike traditional meta-analysis, RMA balances a quick time to production with reasonable data quality assurances, leveraging artificial intelligence (AI) to strike this balance.

Authors

  • Matthew Michelson
    Evid Science, Los Angeles, CA, United States.
  • Tiffany Chow
    Evid Science, El Segundo, CA, United States.
  • Neil A Martin
    Pacific Neuroscience Institute, Providence St John's Health Center, Santa Monica, CA, United States.
  • Mike Ross
    Evid Science, El Segundo, CA, United States.
  • Amelia Tee Qiao Ying
    Evid Science, El Segundo, CA, United States.
  • Steven Minton
    InferLink, El Segundo, CA, United States.

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