Identification and prediction of Parkinson’s disease subtypes and progression using machine learning in two cohorts

The clinical manifestations of Parkinson’s disease (PD) are characterized by heterogeneity in age at onset, disease duration, rate of progression, and the constellation of motor versus non-motor features. There is an unmet need for the characterization of distinct disease subtypes as well as improve...

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Detalles Bibliográficos
Autores principales: Dadu, Anant, Satone, Vipul, Kaur, Rachneet, Hashemi, Sayed Hadi, Leonard, Hampton, Iwaki, Hirotaka, Makarious, Mary B., Billingsley, Kimberley J., Bandres‐Ciga, Sara, Sargent, Lana J., Noyce, Alastair J., Daneshmand, Ali, Blauwendraat, Cornelis, Marek, Ken, Scholz, Sonja W., Singleton, Andrew B., Nalls, Mike A., Campbell, Roy H., Faghri, Faraz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758217/
https://www.ncbi.nlm.nih.gov/pubmed/36526647
http://dx.doi.org/10.1038/s41531-022-00439-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758217/
https://www.ncbi.nlm.nih.gov/pubmed/36526647
http://dx.doi.org/10.1038/s41531-022-00439-z

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