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SOTA Alzheimer's disease classification benchmarks and papers with code | Wizwand
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Alzheimer's disease classification
Benchmarks
Dataset Name
SOTA Method
Dataset Name
SOTA Method
Metric
Trend
Results
Last Updated
TADPOLE
Spectral-GCN
AUC
100
28
1mo ago
ADNI 137 (test)
T1 Only (Augmented)
Accuracy
0.7139
23
1mo ago
NACC n=289 (test)
MATCH-AD
Accuracy
0.984
13
1mo ago
NACC 90% Labels (test)
MATCH-AD
Accuracy
95
9
1mo ago
NACC 80% Labels (test)
MATCH-AD
Accuracy
91.9
9
1mo ago
NACC 60% Labels (test)
MATCH-AD
Accuracy
85
9
1mo ago
NACC 40% Labels (test)
MATCH-AD
Accuracy
76.8
9
1mo ago
NACC 20% Labels (test)
MATCH-AD
Accuracy
68.8
9
1mo ago
NACC 5% Labels (test)
RandomForest
Accuracy
63.3
9
1mo ago
GSE140831 (test)
engGNN
Accuracy
78.8
7
1mo ago
OASIS MRI (90:10)
TDA+DenseNet121
Accuracy
99.93
6
1mo ago
OASIS MRI (80:20)
Novel CNN Architecture
Accuracy
98.92
6
1mo ago
BRISC 2025
PseudoColorViT
Precision
98.99
4
25d ago
Kaggle Alzheimer's Clinical Dataset (test)
Gradient Boosting
Accuracy
86.07
4
1mo ago
OASIS Kaggle MRI (70:30)
CNN (DA + augmentation)
Accuracy
99.68
3
1mo ago
OASIS-1 235 subjects (5-fold subject CV)
Multi-modal 3D CNN
Accuracy
72.34
1
1mo ago
OASIS-1 200 subjects (subject-level split)
VGG16, VGG19, ResNet-18
Accuracy
66
1
1mo ago
OASIS-1 416 subjects (subject-level 5-fold CV)
InceptionV3, Xception
Accuracy
63
1
1mo ago
OASIS-1 (80:20)
PseudoColorViT-Alz
Accuracy
99.79
1
1mo ago
ADNI 859 (test)
T1 Only†
Accuracy
58.6
1
1mo ago
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