Machine Learning-Driven GLCM Analysis of Structural MRI for Alzheimer’s Disease Diagnosis
For the pair <i>AD</i> vs. <i>MCI</i>, the proposed model outperformed state-of-the-art imaging source studies by 0.1% and non-imaging source studies by 4.6%. These results are particularly significant in the field of AD classification, opening the door to more efficient early diagnosis in real-world settings since MCI is considered a precursor to AD.
Authors
- Pedro Ribeiro (ORCID: https://orcid.org/0000-0001-8236-2563)
- Pedro Henrique Fernandes Rodrigues (ORCID: https://orcid.org/0000-0002-5381-6615)
- M Oliveira (ORCID: https://orcid.org/0009-0009-2215-7803)
Institutions
- Universidade Católica Portuguesa (PT)
Publication Details
- Journal
- Bioengineering
- Published
- 2024-11-15
- DOI
- https://doi.org/10.3390/bioengineering11111153
- Citations
- 9
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 2.23
Funders
- U.S. Department of Defense
- Bristol-Myers Squibb
- Eli Lilly and Company
- Pfizer
- Biogen
- Meso Scale Diagnostics
- BioClinica
- Novartis Pharmaceuticals Corporation
- Eisai
- Servier
- H. Lundbeck A/S
- National Institutes of Health
- Genentech
- Fundação para a Ciência e a Tecnologia