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Sudden Unexpected Death in Epilepsy: A Personalized Prediction Tool.

Ashwani JhaCheongeun OhDale HesdorfferBeate DiehlSasha DevoreMartin J BrodieTorbjörn TomsonJosemir W SanderThaddeus S WalczakOrrin Devinsky
Published in: Neurology (2021)
Even when generalized to unseen data, model predictions are more accurate than population-based estimates of SUDEP. Our tool can enable risk-based stratification for biomarker discovery and interventional trials. With further validation in unrepresented populations, it may be suitable for routine individualized clinical decision-making. Clinicians should consider assessment of multiple risk factors, and not focus only on the frequency of convulsions.
Keyphrases
  • risk factors
  • decision making
  • small molecule
  • high throughput
  • clinical practice
  • high resolution
  • big data
  • artificial intelligence
  • deep learning
  • single cell