Artificial Intelligence Prediction Model of Occurrence of Cerebral Vasospasms Based on Machine Learning.

Journal: Journal of neurological surgery. Part A, Central European neurosurgery
PMID: 39178884

Abstract

BACKGROUND:  Symptomatic cerebral vasospasms are deleterious complication of the rupture of a cerebral aneurysm and potentially lethal. The existing scales used to classify the initial presentation of a subarachnoid hemorrhage (SAH) offer a blink of the outcome and the possibility of occurrence of symptomatic cerebral vasospasms. Altogether, neither are they sufficient to predict outcome or occurrence of events reliably nor do they offer a united front. This study tests the common grading scales and factors that otherwise affect the outcome, in an artificial intelligence (AI) based algorithm to create a reliable prediction model for the occurrence of cerebral vasospasms.

Authors

  • Konstantinos Lintas
    Department of Neurosurgery, Klinikum Dortmund gGmbH, Dortmund, Nordrhein-Westfalen, Germany.
  • Stefan Rohde
    Faculty of Health, School of Medicine, University Witten/Herdecke, Witten, Germany.
  • Anna Mpoukouvala
    Graduate in Statistics and Mathematical Modeling, Aristotle University of Thessaloniki, Thessalonike, Kentrikḗ Makedonía, Greece.
  • Boris El Hamalawi
    Department of Neurosurgery, Klinikum Dortmund gGmbH, Dortmund, Nordrhein-Westfalen, Germany.
  • Robert Sarge
    Department of Neurosurgery, Klinikum Dortmund gGmbH, Dortmund, Nordrhein-Westfalen, Germany.
  • Oliver Marcus Mueller
    Department of Neurosurgery, Klinikum Dortmund gGmbH, Dortmund, Nordrhein-Westfalen, Germany.

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