Physical activity and the outcome of cognitive trajectory: a machine learning approach
Abstract Background Physical activity (PA) may have an impact on cognitive function. Machine learning (ML) techniques are increasingly used in dementia research, e.g., for diagnosis and risk stratification. Less is known about the value of ML for predicting cognitive decline in people with dementia...
Saved in:
Main Authors: | Bettina Barisch-Fritz, Jay Shah, Jelena Krafft, Yonas E. Geda, Teresa Wu, Alexander Woll, Janina Krell-Roesch |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2025-01-01
|
Series: | European Review of Aging and Physical Activity |
Subjects: | |
Online Access: | https://doi.org/10.1186/s11556-024-00367-2 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The role of sleep in Alzheimer’s disease: a mini review
by: Jay Pathmanathan, et al.
Published: (2025-02-01) -
Modern Imaging Methods in the Diagnosis of Neurodegenerative Diseases
by: Paulina Dorota Pietrukaniec, et al.
Published: (2025-02-01) -
Brain 18FDG-PET pattern in cognitively impaired elderly patients with bipolar disorder
by: Nouredine Saleh, et al.
Published: (2024-12-01) -
VDAC1: A Key Player in the Mitochondrial Landscape of Neurodegeneration
by: Shirel Argueti-Ostrovsky, et al.
Published: (2024-12-01) -
Editorial: Oxytosis/ferroptosis: unraveling the mechanisms and its multifaceted role in neurodegenerative diseases
by: Nawab John Dar, et al.
Published: (2025-01-01)