title: [Diagnosis of cerebellum-pontine angle tumors using artificial intelligence techniques].
abstract: We are concerned in this paper with learning classification procedures from known cases. More precisely, we provide a diagnostic model that discriminate between cerebellum-pontine angle (CPA) tumors and otorhinolaryngological (ENT) disorders. Usually, in order to distinguish between CPA tumors and ENT disorders one must perform clinical-neurological examination together with expensive radiological imagery (CT and MRI). The proposed model was obtained through artificial intelligence methods and presented a good accuracy level (88.4%) when tested against new cases, considering only clinical examination without radiological imagery results.
authors.affiliation: Departamento de Cirurgia, Faculdade de Medicina, Universidade Federal do Ceará (UFC).
authors.forename: F
authors.initials: F
authors.lastname: Leitão
authors.forename: F C
authors.initials: FC
authors.lastname: Gomes
authors.forename: S
authors.initials: S
authors.lastname: Diógenes
authors.forename: F
authors.initials: F
authors.lastname: Leitão Filho
mesh_terms: D001185:Artificial Intelligence; D002528:Cerebellar Neoplasms / Q000175:diagnosis*; D002530:Cerebellopontine Angle; D003661:Decision Support Techniques; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010038:Otorhinolaryngologic Diseases / Q000175:diagnosis*