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 F-18-FDG PET studies of a model of a brain tumour implantation.

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

Gallivanone F;Valtorta S;Moresco R;Gilardi M C;Castiglioni I
2012

Abstract

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 F-18-FDG PET studies of a model of a brain tumour implantation.
2012
Istituto di Bioimmagini e Fisiologia Molecolare - IBFM
978-1-4577-1787-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/248799
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