title: Data Mining Techniques Applied to Hydrogen Lactose Breath Test.
abstract: OBJECTIVE
  Analyze a set of data of hydrogen breath tests by use of data mining tools. Identify new patterns of H2 production.
  
  
  METHODS
  Hydrogen breath tests data sets as well as k-means clustering as the data mining technique to a dataset of 2571 patients.
  
  
  RESULTS
  Six different patterns have been extracted upon analysis of the hydrogen breath test data. We have also shown the relevance of each of the samples taken throughout the test.
  
  
  CONCLUSIONS
  Analysis of the hydrogen breath test data sets using data mining techniques has identified new patterns of hydrogen generation upon lactose absorption. We can see the potential of application of data mining techniques to clinical data sets. These results offer promising data for future research on the relations between gut microbiota produced hydrogen and its link to clinical symptoms.
authors.affiliation: Department of Computer Languages and Systems, University of Sevilla, Sevilla, Spain.
authors.forename: Cristina
authors.initials: C
authors.lastname: Rubio-Escudero
authors.affiliation: Hispalense Pediatrics Institute, Sevilla, Spain.
authors.forename: Justo
authors.initials: J
authors.lastname: Valverde-Fernández
authors.affiliation: Department of Computer Languages and Systems, University of Sevilla, Sevilla, Spain.
authors.forename: Isabel
authors.initials: I
authors.lastname: Nepomuceno-Chamorro
authors.affiliation: Department of Computer Languages and Systems, University of Sevilla, Sevilla, Spain.
authors.forename: Beatriz
authors.initials: B
authors.lastname: Pontes-Balanza
authors.affiliation: Department of Networks, University Ciego de Ávila, Ciego de Ávila, Cuba.
authors.forename: Yoedusvany
authors.initials: Y
authors.lastname: Hernández-Mendoza
authors.affiliation: Hispalense Pediatrics Institute, Sevilla, Spain.
authors.forename: Alfonso
authors.initials: A
authors.lastname: Rodríguez-Herrera
mesh_terms: D000293:Adolescent; D001944:Breath Tests / Q000379:methods*; D002648:Child; D002675:Child, Preschool; D057225:Data Mining; D005260:Female; D000069196:Gastrointestinal Microbiome; D006801:Humans; D007223:Infant; D007787:Lactose Intolerance / Q000175:diagnosis*; D008297:Male