A Decision Support System for the assisted diagnosis of brain tumors: a feasibility study for ¹⁸F-FDG PET preclinical studies

Autor:	Grosso, E, Lopez, M, SALVATORE, CHRISTIAN, Gallivanone, F, Di Grigoli, G, Valtorta, Silvia, MORESCO, ROSA MARIA, GILARDI, MARIA CARLA, Ramirez, J, Gorriz, JM, Castiglioni, I.
Přispěvatelé:	Grosso, E, Lopez, M, Salvatore, C, Gallivanone, F, Di Grigoli, G, Valtorta, S, Moresco, R, Gilardi, M, Ramirez, J, Gorriz, J, Castiglioni, I
Rok vydání:	2013
Předmět:	Principal Component Analysis Brain Neoplasms Fluorodeoxyglucose F18 Positron-Emission Tomography Disease Progression Machine learning PET brain tumor preclinical Decision Support System Humans Decision Support Systems Clinical Sensitivity and Specificity Algorithms
Zdroj:	Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2012
ISSN:	2694-0604
Popis:	Decision support systems for the assisted medical diagnosis offer the main feature of giving assessments which are poorly affected from arbitrary clinical reasoning. Aim of this work was to assess the feasibility of a decision support system for the assisted diagnosis of brain cancer, such approach presenting potential for early diagnosis of tumors and for the classification of the degree of the disease progression. For this purpose, a supervised learning algorithm combined with a pattern recognition method was developed and cross-validated in ¹⁸F-FDG PET studies of a model of a brain tumour implantation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::5854a2e825bb12549025b691bc3571c2 https://pubmed.ncbi.nlm.nih.gov/23367359 Zobrazit plný text záznamu