Explainable AI to improve acceptance of convolutional neural networks for automatic classification of dopamine transporter SPECT in the diagnosis of clinically uncertain parkinsonian syndromes

PURPOSE: Deep convolutional neural networks (CNN) provide high accuracy for automatic classification of dopamine transporter (DAT) SPECT images. However, CNN are inherently black-box in nature lacking any kind of explanation for their decisions. This limits their acceptance for clinical use. This st...

Descripción completa

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: Springer Berlin Heidelberg 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921148/
https://www.ncbi.nlm.nih.gov/pubmed/34651223
http://dx.doi.org/10.1007/s00259-021-05569-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921148/
https://www.ncbi.nlm.nih.gov/pubmed/34651223
http://dx.doi.org/10.1007/s00259-021-05569-9

Ejemplares similares