PCA and logistic regression in 2-[ 18 F]FDG PET neuroimaging as an interpretable and diagnostic tool for Alzheimer's disease.
Carlos Eduardo Gonçalves de OliveiraWhemberton Martins de AraújoAna Beatriz Marinho de Jesus TeixeiraGustavo Lopes GonçalvesEmerson Nobuyuki ItikawaPublished in: Physics in medicine and biology (2023)
our classification model was trained on publicly available and robust data and tested, with good results, on clinical routine data. Our study shows that it serves as a powerful and interpretable tool capable of assisting in the diagnosis of AD in the possession of FDG PET neuroimages. The relationship between classification model output scores and AD progression can and should be explored in future studies.