Forecasting individual progression trajectories in Alzheimer’s disease
Accurate prediction of disease progression in Alzheimer’s disease (AD) is necessary for optimal recruitment of patients to clinical trials. Here, the authors present AD Course Map, a statistical model which helps to predict disease progression in participants, thus decreasing the required sample siz...
Main Authors: | Etienne Maheux, Igor Koval, Juliette Ortholand, Colin Birkenbihl, Damiano Archetti, Vincent Bouteloup, Stéphane Epelbaum, Carole Dufouil, Martin Hofmann-Apitius, Stanley Durrleman |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-02-01
|
Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-022-35712-5 |
Similar Items
-
Understanding factors associated with the trajectory of subjective cognitive complaints in groups with similar objective cognitive trajectories
by: Federica Cacciamani, et al.
Published: (2023-11-01) -
Forecasting individual progression trajectories in Huntington disease enables more powered clinical trials
by: Igor Koval, et al.
Published: (2022-11-01) -
Changes in the use of psychotropic drugs during the course of Alzheimer's disease: A large‐scale longitudinal study of French medical records
by: Manon Ansart, et al.
Published: (2021-01-01) -
Impact of sex and APOE-ε4 genotype on patterns of regional brain atrophy in Alzheimer's disease and healthy aging
by: Benoît Sauty, et al.
Published: (2023-06-01) -
Understanding the Variability in Graph Data Sets through Statistical Modeling on the Stiefel Manifold
by: Clément Mantoux, et al.
Published: (2021-04-01)