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References from Explainable machine learning for Alzheimer's disease characterization using small-sample EEG data. Local targets link to admitted publications; unresolved targets remain external evidence.
From amyloid to synaptic dysfunction: biomarker-driven insights into Alzheimer's disease
10.3390/cimb47080580 · 2025 · External reference
Unlocking the potential of EEG in Alzheimer's disease research: current status and pathways to precision detection
10.1016/j.brainresbull.2025.111281 · 2025 · External reference
EEG-based Alzheimer's disease detection: past, present, and future
10.1016/j.measurement.2025.120096 · 2026 · External reference
Permutation entropy: a natural complexity measure for time series
10.1103/physrevlett.88.174102 · 2002 · External reference
Data leakage in deep learning studies of translational EEG
10.3389/fnins.2024.1373515 · 2024 · External reference
EEG entropy insights in the context of physiological aging and Alzheimer's and Parkinson's diseases: a comprehensive review
10.1007/s11357-024-01185-1 · 2024 · External reference
PRISMA systematic review of electroencephalographic (EEG) microstates as biomarkers: secondary findings in memory functions
10.3390/neurolint17100160 · 2025 · External reference
EEG microstate differences between Alzheimer's disease, frontotemporal dementia, and healthy controls using 4 and 7 clustering classes with a ratio approach
10.3390/medicina61111917 · 2025 · External reference
Support-vector networks
10.1023/a:1022627411411 · 1995 · External reference
The role of data partitioning on the performance of EEG-based deep learning models in supervised cross-subject analysis: a preliminary study
10.1016/j.compbiomed.2025.110608 · 2025 · External reference
Fully automated discrimination of Alzheimer's disease using resting-state electroencephalography signals
10.21037/qims-21-430 · 2022 · External reference
Not all entropy is equal: Parameter sensitivity, ordinal blindness, and the case for sample entropy in dementia EEG
10.64898/2026.03.09.26347355 · 2026 · External reference
Regularization paths for generalized linear models via coordinate descent
10.18637/jss.v033.i01 · 2010 · External reference
Integrative and interpretable framework to unveil the neurophysiological fingerprint of Alzheimer's disease and mild cognitive impairment: A machine learning-SHAP approach
10.1016/j.bbe.2025.05.011 · 2025 · External reference
Current status of fluid biomarkers for early Alzheimer's disease and FDA regulation implications
10.1016/j.jns.2024.123325 · 2024 · External reference
Assessing the potential of data augmentation in EEG functional connectivity for early detection of Alzheimer's disease
10.1007/s12559-023-10188-7 · 2024 · External reference
Electroencephalography-based classification of Alzheimer's disease spectrum during computer-based cognitive testing
10.1038/s41598-024-55656-8 · 2024 · External reference
On a test of whether one of two random variables is stochastically larger than the other
10.1214/aoms/1177730491 · 1947 · External reference
The diagnosis of dementia due to Alzheimer's disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease
10.1016/j.jalz.2011.03.005 · 2011 · External reference
Comparison of cerebrospinal fluid, plasma and neuroimaging biomarker utility in Alzheimer's disease
10.1093/braincomms/fcae081 · 2024 · External reference
EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: a review
10.1016/j.neuroimage.2017.11.062 · 2018 · External reference
A dataset of scalp EEG recordings of Alzheimer's disease, frontotemporal dementia and healthy subjects from routine EEG
10.3390/data8060095 · 2023 · External reference
A systematic review and methodological analysis of EEG-based biomarkers of Alzheimer's disease
10.1016/j.measurement.2023.113274 · 2023 · External reference
Current screening tests/biomarkers for Alzheimer's Disease: Implications for clinicians
2024 · External reference
Cognitive adaptations for memory deficits in MCI and AD patients: a meta-analysis of EEG microstates
10.1016/j.nicl.2025.103929 · 2026 · External reference
Education bias in typical brief cognitive tests used for the detection of dementia in elderly population with low educational level: a critical review
10.1080/23279095.2022.2155521 · 2025 · External reference
Time-frequency domain analysis of quantitative electroencephalography as a biomarker for dementia
10.3390/diagnostics15121509 · 2025 · External reference
Cross-validation failure: small sample sizes lead to large error bars
10.1016/j.neuroimage.2017.06.061 · 2018 · External reference
Interpreting artificial intelligence models: a systematic review on the application of LIME and SHAP in Alzheimer's disease detection
10.1186/s40708-024-00222-1 · 2024 · External reference
Explainable artificial intelligence in Alzheimer's disease classification: a systematic review
10.1007/s12559-023-10192-x · 2024 · External reference
A deep learning model for the detection of various dementia and MCI pathologies based on resting-state electroencephalography data: A retrospective multicentre study
10.1016/j.neunet.2023.12.009 · 2024 · External reference
The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms
10.1109/tau.1967.1161901 · 1967 · External reference
10.1017/s0033291724001132
10.1017/s0033291724001132 · 2024 · External reference
Resting-state EEG microstate features for Alzheimer's disease classification
10.1371/journal.pone.0311958 · 2024 · External reference
Diagnosis of Alzheimer's disease via resting-state EEG: integration of spectrum, complexity, and synchronization signal features
10.3389/fnagi.2023.1288295 · 2023 · External reference
