Multivariate longitudinal clustering reveals neuropsychological factors as dementia predictors in an Alzheimer’s disease progression study
Abstract Dementia due to Alzheimer’s disease (AD) is a multifaceted neurodegenerative disorder characterized by various cognitive and behavioral decline factors. In this work, we propose an extension of the traditional k-means clustering for multivariate time series data to cluster joint trajectorie...
Saved in:
| Main Authors: | Patrizia Ribino, Claudia Di Napoli, Giovanni Paragliola, Davide Chicco, Francesca Gasparini |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-03-01
|
| Series: | BioData Mining |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13040-025-00441-0 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Brazilian version of the Mattis dementia rating scale: diagnosis of mild dementia in Alzheimer's disease
by: Cláudia S. Porto, et al.
Published: (2003-06-01) -
A Comparison of Machine Learning Algorithms for Predicting Alzheimer’s Disease Using Neuropsychological Data
by: Zakaria Mokadem, et al.
Published: (2024-12-01) -
A longitudial study of a neuropsychological rehabilitation program in Alzheimer's disease Estudo longitudinal de um programa de reabilitação neuropsicológica dirigido a pacientes com doença de Alzheimer
by: Jacqueline Abrisqueta-Gomez, et al.
Published: (2004-09-01) -
Quantity and Quality Matter: Different Neuroanatomical Substrates of Apathy in Alzheimer’s Disease and Behavioural Variant Frontotemporal Dementia
by: Luciano Inácio Mariano, et al.
Published: (2025-04-01) -
The assessment and management of dementia
by: Zahir Vally
Published: (2010-10-01)