Commentary: Machine Learning-Driven Metabolomic Evaluation of Cerebrospinal Fluid: Insights into Poor Outcomes after Aneurysmal Subarachnoid Hemorrhage

Mark N. Pernik, Jeffrey I. Traylor, Tarek Y. El Ahmadieh, Carlos A. Bagley, Salah G. Aoun

Research output: Contribution to journalComment/debatepeer-review

Original languageEnglish (US)
Pages (from-to)E410-E411
JournalNeurosurgery
Volume88
Issue number5
DOIs
StatePublished - May 1 2021

Keywords

  • Artificial intelligence
  • Cerebrospinal fluid
  • Machine learning
  • Subarachnoid hemorrhage

ASJC Scopus subject areas

  • Surgery
  • Clinical Neurology

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