Data-driven subtyping of Parkinson's disease using MRI: current insights, challenges, and future directions.

Vijayakumari AA, Sakaie KE, Fernandez HH, Walter BL

DOI: 10.3389/fnagi.2026.1819248
Published: 2026
Container: Frontiers in aging neuroscience
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fnagi.2026.1819248,
  title = {Data-driven subtyping of Parkinson's disease using MRI: current insights, challenges, and future directions.},
  author = {Vijayakumari AA and Sakaie KE and Fernandez HH and Walter BL},
  year = {2026},
  journal = {Frontiers in aging neuroscience},
  doi = {10.3389/fnagi.2026.1819248},
  url = {https://doi.org/10.3389/fnagi.2026.1819248}
}

RIS

TY  - JOUR
TI  - Data-driven subtyping of Parkinson's disease using MRI: current insights, challenges, and future directions.
AU  - Vijayakumari AA
AU  - Sakaie KE
AU  - Fernandez HH
AU  - Walter BL
PY  - 2026
JO  - Frontiers in aging neuroscience
DO  - 10.3389/fnagi.2026.1819248
UR  - https://doi.org/10.3389/fnagi.2026.1819248
ER  -

APA

AA, V., KE, S., HH, F., & BL, W. (2026). Data-driven subtyping of Parkinson's disease using MRI: current insights, challenges, and future directions.. Frontiers in aging neuroscience. https://doi.org/10.3389/fnagi.2026.1819248

Source records

pubmed · retrieved 2026-09-25T16:19:51.506Z