A Decision Support System for the assisted diagnosis of brain tumors: a feasibility study for ¹⁸F-FDG PET preclinical studies.
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.
University of Milan-Bicocca, Milan, Italy. grosso.eleonora@ hsr.it
E
E
Grosso
M
M
López
C
C
Salvatore
F
F
Gallivanone
G
G
Di Grigoli
S
S
Valtorta
R
R
Moresco
M C
MC
Gilardi
J
J
Ramírez
J M
JM
Górriz
I
I
Castiglioni
D000465:Algorithms; D001932:Brain Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D020000:Decision Support Systems, Clinical; D018450:Disease Progression; D019788:Fluorodeoxyglucose F18; D006801:Humans; D049268:Positron-Emission Tomography / Q000379:methods*; D025341:Principal Component Analysis; D012680:Sensitivity and Specificity
D019788:Fluorodeoxyglucose F18