Data-Driven Subtyping of Parkinson’s Disease Using Longitudinal Clinical Records: A Cohort Study
Abstract Parkinson’s disease (PD) is associated with diverse clinical manifestations including motor and non-motor signs and symptoms, and emerging biomarkers. We aimed to reveal the heterogeneity of PD to define subtypes and their progression rates using an automated deep learning algorithm on the...
Guardado en:
Autores principales: | Xi Zhang, Jingyuan Chou, Jian Liang, Cao Xiao, Yize Zhao, Harini Sarva, Claire Henchcliffe, Fei Wang |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2019
|
Materias: | |
Acceso en línea: | https://doaj.org/article/ff625ebf1c6a430db23123280e2cc6c6 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Comprehensive subtyping of Parkinson’s disease patients with similarity fusion: a case study with BioFIND data
por: Matthew Brendel, et al.
Publicado: (2021) -
Rasagiline in treatment of Parkinson’s disease
por: Lakshmi Nayak, et al.
Publicado: (2008) -
Data-driven identification of subtypes of intimate partner violence
por: Ahmet Mert Hacıaliefendioğlu, et al.
Publicado: (2021) -
Data-driven detection of subtype-specific differentially expressed genes
por: Lulu Chen, et al.
Publicado: (2021) -
Longitudinal evolution of non-motor symptoms in early Parkinson’s disease: a 3-year prospective cohort study
por: Ruwei Ou, et al.
Publicado: (2021)