Construction and validation of an algorithm to separate focal and generalised epilepsy using clinical variables: A comparison of machine learning approaches.

Journal: Epilepsy & behavior : E&B
PMID: 38669972

Abstract

PURPOSE: Epilepsy type, whether focal or generalised, is important in deciding anti-seizure medication (ASM). In resource-limited settings, investigations are usually not available, so a clinical separation is required. We used a naïve Bayes approach to devise an algorithm to do this, and compared its accuracy with algorithms devised by five other machine learning methods.

Authors

  • Victor Patterson
    Independent Neurologist, Belfast, UK. Electronic address: vhp498@gmail.com.
  • David H Glass
    School of Computing, Ulster University, Belfast, UK.
  • Shambhu Kumar
    Department of Neurology, All India Institute of Medical Sciences, New Delhi, India.
  • Sarah Misbah El-Sadig
    Department of Medicine, University of Khartoum, Khartoum, Sudan.
  • Inaam Mohamed
    Department of Paediatrics, University of Khartoum, Khartoum, Sudan.
  • Rahba El-Amin
    Department of Medicine, University of Khartoum, Khartoum, Sudan.
  • Mamta Singh
    Amity Institute of Molecular Medicine and Stem Cell Research Amity University UP, Sector-125, Noida 201313, India.

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