Adapting to evolving MRI data: A transfer learning approach for Alzheimer’s disease prediction
Integrating 3D magnetic resonance imaging (MRI) with machine learning has shown promising results in healthcare, especially in detecting Alzheimer’s Disease (AD). However, changes in MRI technologies and acquisition protocols often yield limited data, leading to potential overfitting. This study exp...
Saved in:
Main Authors: | Rosanna Turrisi, Sarthak Pati, Giovanni Pioggia, Gennaro Tartarisco |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-02-01
|
Series: | NeuroImage |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811925000163 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Transforming Alzheimer’s Disease Diagnosis: Implementing Vision Transformer (ViT) for MRI Images Classification
by: Dian Kurniasari, et al.
Published: (2025-01-01) -
The roles of universities in virtual intellectual migration via evolving technologies and STEM
by: Beverly Lindsay
Published: (2024-03-01) -
Towards a Standard Benchmarking Framework for Domain Adaptation in Intelligent Fault Diagnosis
by: Mohammed M. Farag
Published: (2025-01-01) -
Evaluation of centering ability of XP endo shaper, Edge Evolve and Hyflex CM in simulated curved canals
by: Van B. Werdina, et al.
Published: (2019-06-01) -
An attention based residual U-Net with swin transformer for brain MRI segmentation
by: Tazkia Mim Angona, et al.
Published: (2025-03-01)