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Assessing the effects of therapeutic combinations on SARS-CoV-2 infected patient outcomes: A big data approach.

Hamidreza MoradiH Timothy BunnellBradley S PriceMaryam KhodaverdiMichael T VestJ Zachary PorterfieldAlfred Jerrod AnzaloneSusan L SantangeloWesley KimbleJeremy HarperWilliam B HillegassSally L Hoddernull null
Published in: PloS one (2023)
This machine learning model by accurately predicting the mortality provides insights about the treatment combinations associated with clinical improvement in COVID-19 patients. Analysis of the model's components suggests benefit to treatment with combination of steroids, antivirals, and anticoagulant medication. The approach also provides a framework for simultaneously evaluating multiple real-world therapeutic combinations in future research studies.
Keyphrases
  • big data
  • sars cov
  • machine learning
  • artificial intelligence
  • healthcare
  • atrial fibrillation
  • cardiovascular disease
  • venous thromboembolism
  • cardiovascular events
  • respiratory syndrome coronavirus
  • combination therapy