Data-driven identification of diagnostically useful extrastriatal signal in dopamine transporter SPECT using explainable AI

This study used explainable artificial intelligence for data-driven identification of extrastriatal brain regions that can contribute to the interpretation of dopamine transporter SPECT with (123)I-FP-CIT in parkinsonian syndromes. A total of 1306 (123)I-FP-CIT-SPECT were included retrospectively. B...

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Detalles Bibliográficos
Autores principales: Nazari, Mahmood, Kluge, Andreas, Apostolova, Ivayla, Klutmann, Susanne, Kimiaei, Sharok, Schroeder, Michael, Buchert, Ralph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8617288/
https://www.ncbi.nlm.nih.gov/pubmed/34824352
http://dx.doi.org/10.1038/s41598-021-02385-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8617288/
https://www.ncbi.nlm.nih.gov/pubmed/34824352
http://dx.doi.org/10.1038/s41598-021-02385-x

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