Using a Bayesian workflow approach to define the optimal level of anatomy/functionality voxels clustering for the prediction of tau propagation and cortical loss in Alzheimer's disease
Jean‐Paul Soucy, Clyde J Belasso, Zhengchen Cai, Gleb Bezgin, Jenna Stevenson, Nesrine Rahmouni, Cécile Tissot, Firoza Z Lussier, Pedro Rosa‐Neto, Hassan J Rivaz, Habib Benali · 2025
Read Using a Bayesian workflow approach to define the optimal level of anatomy/functionality voxels clustering for the prediction of tau propagation and cortical loss in Alzheimer's disease by Jean‐Paul Soucy, Clyde J Belasso, Zhengchen Cai, Gleb Bezgin, Jenna Stevenson, Nesrine Rahmouni, Cécile Tissot, Firoza Z Lussier, Pedro Rosa‐Neto, Hassan J Rivaz, Habib Benali (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11712878.txt.
Description
Jean-Paul Soucy and co-authors present a 2025 research paper on how to group brain scan data when modeling the spread of tau in Alzheimer's disease. The team worked with data from the TRIAD cohort at McGill University. The study asks how much fine detail a model needs before its forecasts stop getting better.
Inside, the authors compare four ways of grouping the data, from one pool for the whole brain to groups split by both brain region and brain network. They used scans from 113 people who each had tau PET and MRI at least twice, a year or more apart. The work helps researchers pick a model size that stays accurate without needless cost.
Catalog record
| CREATOR | Jean‐Paul Soucy, Clyde J Belasso, Zhengchen Cai, Gleb Bezgin, Jenna Stevenson, Nesrine Rahmouni, Cécile Tissot, Firoza Z Lussier, Pedro Rosa‐Neto, Hassan J Rivaz, Habib Benali |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 3 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |