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Machine learning based prediction of length of stay in acute ischaemic stroke of the anterior circulation in patients treated with thrombectomy.

Ludger FeyenJan Pinz-BogesitsChristian BlockhausMarcus KatohPatrick HaageLouisa NitschChristina Schaub
Published in: Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences (2023)
Machine learning has potential use to estimate the length of stay of patients with acute ischaemic stroke that were treated with thrombectomy.
Keyphrases
  • machine learning
  • acute ischemic stroke
  • artificial intelligence
  • liver failure
  • big data
  • respiratory failure
  • deep learning
  • drug induced
  • aortic dissection
  • risk assessment
  • hepatitis b virus
  • climate change