Improvement of classification performance of Parkinson’s disease using shape features for machine learning on dopamine transporter single photon emission computed tomography

OBJECTIVE: To assess the classification performance between Parkinson’s disease (PD) and normal control (NC) when semi-quantitative indicators and shape features obtained on dopamine transporter (DAT) single photon emission computed tomography (SPECT) are combined as a feature of machine learning (M...

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Detalles Bibliográficos
Autores principales: Shiiba, Takuro, Arimura, Yuki, Nagano, Miku, Takahashi, Tenma, Takaki, Akihiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980558/
https://www.ncbi.nlm.nih.gov/pubmed/31978154
http://dx.doi.org/10.1371/journal.pone.0228289

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980558/
https://www.ncbi.nlm.nih.gov/pubmed/31978154
http://dx.doi.org/10.1371/journal.pone.0228289

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