title: Selecting anti-epileptic drugs: a pediatric epileptologist's view, a computer's view.
abstract: OBJECTIVE
  To identify which clinical characteristics are important to include in clinical decision support systems developed for Antiepileptic Drug (AEDs) selection.
  
  
  METHODS
  Twenty-three epileptologists from the Childhood Absence Epilepsy network completed a survey related to AED selection. Using cluster analysis their responses where classified into subject matter groups and weighted for importance.
  
  
  RESULTS
  Five distinct subject matter groups were identified and their relative weighting for importance were determined: disease characteristics (weight 4.8 ± 0.049), drug toxicities (3.82 ± 0.098), medical history (3.12 ± 0.102), systemic characteristics (2.57 ± 0.048) and genetic characteristics (1.08 ± 0.046).
  
  
  CONCLUSIONS
  Research about prescribing patterns exists but research on how such data can be used to train advanced technology is novel. As machine learning algorithms becomes more and more prevalent in clinical decisions support systems, developing methods for determining which data should be part of those algorithms is equally important.
authors.affiliation: Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. john.pestian@cchmc.org
authors.forename: J
authors.initials: J
authors.lastname: Pestian
authors.forename: P
authors.initials: P
authors.lastname: Matykiewicz
authors.forename: K
authors.initials: K
authors.lastname: Holland-Bouley
authors.forename: S
authors.initials: S
authors.lastname: Standridge
authors.forename: M
authors.initials: M
authors.lastname: Spencer
authors.forename: T
authors.initials: T
authors.lastname: Glauser
mesh_terms: D000465:Algorithms; D000927:Anticonvulsants / Q000627:therapeutic use*; D001185:Artificial Intelligence; D016000:Cluster Analysis; D020000:Decision Support Systems, Clinical; D004827:Epilepsy / Q000188:drug therapy; D005260:Female; D006801:Humans; D008297:Male; D010820:Physicians; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*
chemical_list: D000927:Anticonvulsants