title: Clinical mass spectrometry proteomic diagnosis by conformal predictors.
abstract: The paper describes an application of conformal predictors to diagnose breast cancer using proteomic mass spectrometry data provided by Leiden University Medical Center. Unlike many conventional classification systems, this approach allows us not just to classify samples, but add valid measures of confidence in our predictions for individual patients.
authors.affiliation: Royal Holloway, University of London. alex@cs.rhul.ac.uk
authors.forename: Alex
authors.initials: A
authors.lastname: Gammerman
authors.forename: Ilia
authors.initials: I
authors.lastname: Nouretdinov
authors.forename: Brian
authors.initials: B
authors.lastname: Burford
authors.forename: Alexey
authors.initials: A
authors.lastname: Chervonenkis
authors.forename: Vladimir
authors.initials: V
authors.lastname: Vovk
authors.forename: Zhiyuan
authors.initials: Z
authors.lastname: Luo
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000378:metabolism; D005260:Female; D006801:Humans; D020543:Proteome / Q000032:analysis*; D040901:Proteomics; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
chemical_list: D020543:Proteome