title: Diagnosing scrapie in sheep: a classification experiment.
abstract: Scrapie is a neuro-degenerative disease in small ruminants. A data set of 3113 records of sheep reported to the Scrapie Notifications Database in Great Britain has been studied. Clinical signs were recorded as present/absent in each animal by veterinary officials (VO) and a post-mortem diagnosis was made. In an attempt to detect healthy animals within the set of suspects using only the clinical signs, 18 classification methods were applied ranging from simple linear classifiers to classifier ensembles such as Bagging, AdaBoost and Random Forests. The results suggest that the clinical classification by the VO was adequate as no further differentiation within the set of suspects was feasible.
authors.affiliation: School of Informatics, University of Wales, Bangor, UK. l.i.kuncheva@bangor.ac.uk
authors.forename: Ludmila I
authors.initials: LI
authors.lastname: Kuncheva
authors.forename: Victor J
authors.initials: VJ
authors.lastname: del Rio Vilas
authors.forename: Juan J
authors.initials: JJ
authors.lastname: Rodríguez
mesh_terms: D000818:Animals; D003198:Computer Simulation; D016208:Databases, Factual; D003936:Diagnosis, Computer-Assisted / Q000145:classification / Q000706:statistics & numerical data / Q000662:veterinary*; D012372:ROC Curve; D012608:Scrapie / Q000145:classification / Q000175:diagnosis*; D012756:Sheep; D006113:United Kingdom