Detection of Alzheimer’s Disease using Explainable Machine Learning and Mathematical Models

Beyond improved accuracy, our method offers potential for computational efficiency due to dimensionality reduction and provides novel physical insights into AD through inertia tensor analysis.

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Institutions

Publication Details

Journal
Journal of Medical Physics
Published
2025-01-01
DOI
https://doi.org/10.4103/jmp.jmp_128_24
Citations
1
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.84

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article

Detection of Alzheimer’s Disease using Explainable Machine Learning and Mathematical Models

R. Selvakumar, Krishna Mahapatra
1 citations
Journal of Medical Physics
Brain Tumor Detection and Classification
0.84
article

Detection of Alzheimer’s Disease using Explainable Machine Learning and Mathematical Models

R. Selvakumar, Krishna Mahapatra
article en
1 citations

Abstract

Beyond improved accuracy, our method offers potential for computational efficiency due to dimensionality reduction and provides novel physical insights into AD through inertia tensor analysis.

Journal of Medical PhysicsVol. 50(1)
Vellore Institute of Technology University (IN)
VIT University
Openalex Percentile: Top 28%
Brain Tumor Detection and Classification
0.84
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Detection of Alzheimer’s Disease using Explainable Machine Learning and Mathematical Models — R. Selvakumar, Krishna Mahapatra · Journal of Medical Physics (2025) | TGRS Research Map | TGRS