‘Machine Learning’ multiclassification for stage diagnosis of Alzheimer’s disease utilizing augmented blood gene expression and feature fusion
Abstract Objective The present study explores the classification of Alzheimer’s disease (AD) stages, encompassing cognitive normalcy, Mild Cognitive Impairment (MCI), and AD/Dementia, through the application of Machine Learning (ML) multiclassification algorithms. This investigation utilizes blood g...
Saved in:
| Main Authors: | Manash Sarma, Subarna Chatterjee |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-06-01
|
| Series: | Discover Applied Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s42452-025-07237-1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multiclassification of Colorectal Polyps from Colonoscopy Images Using AI for Early Diagnosis
by: Jothiraj Selvaraj, et al.
Published: (2025-05-01) -
Advancing Ovarian Cancer Diagnosis Through Deep Learning and eXplainable AI: A Multiclassification Approach
by: Meera Radhakrishnan, et al.
Published: (2024-01-01) -
Tau mediates the reshaping of the transcriptional landscape toward intermediate Alzheimer’s disease stages
by: Giacomo Siano, et al.
Published: (2025-01-01) -
Etiology of Late-Onset Alzheimer’s Disease, Biomarker Efficacy, and the Role of Machine Learning in Stage Diagnosis
by: Manash Sarma, et al.
Published: (2024-11-01) -
FOCC: A Synthetically Balanced Federated One-Class-Classification for Cyber Threat Intelligence in Software Defined Networking
by: Syed Hussain Ali Kazmi, et al.
Published: (2025-01-01)