title: Direct explanations for the development and use of a multi-layer perceptron network that classifies low-back-pain patients.
abstract: Using a new method published by the first author, this article shows how direct explanations can be provided to interpret the classification of any input case by a standard multilayer perceptron (MLP) network. The method is demonstrated for a real-world MLP that classifies low-back-pain patients into three diagnostic classes. The application of the method leads to the discovery of a number of mis-diagnosed training and test cases and to the development of a more optimal low-back-pain MLP network.
authors.affiliation: Cranfield University (RMCS), Shrivenham, Swindon SN6 8LA, UK. vaughn@rmcs.cranfield.ac.uk
authors.forename: M L
authors.initials: ML
authors.lastname: Vaughn
authors.forename: S J
authors.initials: SJ
authors.lastname: Cavill
authors.forename: S J
authors.initials: SJ
authors.lastname: Taylor
authors.forename: M A
authors.initials: MA
authors.lastname: Foy
authors.forename: A J
authors.initials: AJ
authors.lastname: Fogg
mesh_terms: D006801:Humans; D017116:Low Back Pain / Q000145:classification*; D016571:Neural Networks, Computer