title: [The results of quantitative cytological analysis of the structure of follicular thyroid tumors using computer and neural network technologies].
abstract: Artificial neural network is a complex system capable of gathering and synthesizing data and capable of learning using particular given parameters. This technology was applied to studying cytological diagnostics of thyroid diseases to differentiate between follicular cancer and follicular adenoma. A complex of quantitative cytological characteristics was used to describe cytological preparations by examples of known cytological diagnosis to train the neural network. Among offered cytological examples, 96% were recognized correctly during testing.
authors.forename: T L
authors.initials: TL
authors.lastname: Poloz
authors.forename: V A
authors.initials: VA
authors.lastname: Shkurupiĭ
authors.forename: V V
authors.initials: VV
authors.lastname: Poloz
authors.forename: A V
authors.initials: AV
authors.lastname: Demin
mesh_terms: D018263:Adenocarcinoma, Follicular / Q000473:pathology*; D000236:Adenoma / Q000473:pathology*; D001706:Biopsy; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003937:Diagnosis, Differential; D006801:Humans; D016571:Neural Networks, Computer; D015203:Reproducibility of Results; D012189:Retrospective Studies; D013964:Thyroid Neoplasms / Q000473:pathology*