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Semiquantitative [¹²³I]FP-CIT SPECT metrics combined with machine learning improve clinical differentiation of Parkinson’s disease and atypical parkinsonian syndrome

Title:	Semiquantitative [¹²³I]FP-CIT SPECT metrics combined with machine learning improve clinical differentiation of Parkinson’s disease and atypical parkinsonian syndrome
Authors:	Fernández-Rodríguez, Paula^{Aff1, Aff2}; Franco-Rosado, Pablo^{Aff2, Aff3, Aff4}; Diaz-Galvan, Patricia^{Aff2, Aff3}; Muñoz-Delgado, Laura^{Aff2, Aff3}; Luque-Ambrosiani, Antonio Cristobal^{Aff2, Aff3}; Labrador-Espinosa, Miguel Ángel^{Aff2, Aff5}; Silva-Rodríguez, Jesús^{Aff2, Aff3, Aff6}; Ojeda-Lepe, Elena^{Aff2, Aff3}; Macías-García, Daniel^{Aff2, Aff3}; Adarmes-Gómez, Astrid^{Aff2, Aff3}; Jesús, Silvia^{Aff2, Aff3}; Carrillo, Fátima^{Aff2, Aff3, Aff7}; Lojo-Ramírez, Jose Antonio^Aff1; Solis, David García^Aff1; Grothe, Michel J.^{Aff2, Aff3, Aff6, IDs0025902608022x_cor1}; Mir, Pablo^{Aff2, Aff3, Aff7, IDs0025902608022x_cor2}
Source:	European Journal of Nuclear Medicine and Molecular Imaging. :1-16
Database:	Springer Nature Journals