Automatic migraine classification via feature selection committee and machine learning techniques over imaging and questionnaire data.

Journal: BMC medical informatics and decision making
PMID:

Abstract

BACKGROUND: Feature selection methods are commonly used to identify subsets of relevant features to facilitate the construction of models for classification, yet little is known about how feature selection methods perform in diffusion tensor images (DTIs). In this study, feature selection and machine learning classification methods were tested for the purpose of automating diagnosis of migraines using both DTIs and questionnaire answers related to emotion and cognition - factors that influence of pain perceptions.

Authors

  • Yolanda Garcia-Chimeno
    DeustoTech-LIFE, University of Deusto, Avda Universidades, 24, 48007, Bilbao, Spain.
  • Begonya Garcia-Zapirain
    DeustoTech-LIFE, University of Deusto, Avda Universidades, 24, 48007, Bilbao, Spain.
  • Marian Gomez-Beldarrain
    Service of Neurology Hospital de Galdakao-Usansolo, Barrio Labeaga, S/N, Galdakao, 48960, Spain.
  • Begonya Fernandez-Ruanova
    Service of Neurology Hospital de Galdakao-Usansolo, Barrio Labeaga, S/N, Galdakao, 48960, Spain.
  • Juan Carlos Garcia-Monco
    Research and Innovation Department, Magnetic Resonance Imaging Unit, OSATEK, Alameda Urquijo, 36, Bilbao, 48011, Spain.