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Fully automated discrimination of Alzheimer’s disease using resting-state electroencephalography signals

https://doi.org/10.21037/qims-21-430
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1001/archpsyc.1983.01790060110016openalex-snapshot
The Mini-Mental State Examination
inferredcites →https://doi.org/10.1001/jamaneurol.2021.2161openalex-snapshot
Global Prevalence of Young-Onset Dementia
inferredcites →https://doi.org/10.1002/1097-4679(197810)34:4<816::aid-jclp2270340402>3.0.co;2-qopenalex-snapshot
Wechsler memory scale: A selective review of the literature
inferredcites →https://doi.org/10.1007/978-90-481-9695-1openalex-snapshot
Advances in Cognitive Neurodynamics (II)
inferredcites →https://doi.org/10.1007/978-90-481-9695-1_106openalex-snapshot
On the Early Diagnosis of Alzheimer’s Disease from EEG Signals: A Mini-Review
inferredcites →https://doi.org/10.1007/978-94-009-1217-5_10openalex-snapshot
Principal component analysis
inferredcites →https://doi.org/10.1007/bf00994018openalex-snapshot
Support-Vector Networks
inferredcites →https://doi.org/10.1007/s00429-013-0687-3openalex-snapshot
Latent feature representation with stacked auto-encoder for AD/MCI diagnosis
inferredcites →https://doi.org/10.1007/s00702-003-0024-8openalex-snapshot
EEG coherence in Alzheimer?s dementia
inferredcites →https://doi.org/10.1007/s00702-010-0450-3openalex-snapshot
New diagnostic EEG markers of the Alzheimer’s disease using visibility graph
inferredcites →https://doi.org/10.1007/s100720200003openalex-snapshot
Rey-Osterrieth complex figure: normative values in an Italian population sample
inferredcites →https://doi.org/10.1007/s10548-012-0234-1openalex-snapshot
Clinical Implications of Quantitative Electroencephalography and Current Source Density in Patients with Alzheimer’s Disease
inferredcites →https://doi.org/10.1016/0013-4694(94)90033-7openalex-snapshot
EEG-based, neural-net predictive classification of Alzheimer's disease versus control subjects is augmented by non-linear EEG measures
inferredcites →https://doi.org/10.1016/0013-4694(94)90095-7openalex-snapshot
EEG coherence in Alzheimer disease
inferredcites →https://doi.org/10.1016/j.artmed.2020.101924openalex-snapshot
Detection of early stages of Alzheimer’s disease based on MEG activity with a randomized convolutional neural network
inferredcites →https://doi.org/10.1016/j.clinph.2004.01.001openalex-snapshot
EEG dynamics in patients with Alzheimer's disease
inferredcites →https://doi.org/10.1016/j.clinph.2007.05.070openalex-snapshot
EEG correlates in the spectrum of cognitive decline
inferredcites →https://doi.org/10.1016/j.clinph.2019.07.016openalex-snapshot
Oscillatory connectivity as a diagnostic marker of dementia due to Alzheimer’s disease
inferredcites →https://doi.org/10.1016/j.cmpb.2004.07.002openalex-snapshot
A study on the reference electrode standardization technique for a realistic head model
inferredcites →https://doi.org/10.1016/j.ijpsycho.2005.04.006openalex-snapshot
Brain oscillatory responses to an auditory-verbal working memory task in mild cognitive impairment and Alzheimer's disease
inferredcites →https://doi.org/10.1016/j.ijpsycho.2008.04.004openalex-snapshot
Decreased amplitude of auditory event-related delta responses in Alzheimer's disease
inferredcites →https://doi.org/10.1016/j.ijpsycho.2015.02.008openalex-snapshot
Brain neural synchronization and functional coupling in Alzheimer's disease as revealed by resting state EEG rhythms
inferredcites →https://doi.org/10.1016/j.jalz.2010.11.007openalex-snapshot
National estimates of the prevalence of Alzheimer's disease in the United States
inferredcites →https://doi.org/10.1016/j.jalz.2011.03.005openalex-snapshot
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
inferredcites →https://doi.org/10.1016/j.jneumeth.2003.10.009openalex-snapshot
EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis
inferredcites →https://doi.org/10.1016/j.jneumeth.2006.10.023openalex-snapshot
Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)
inferredcites →https://doi.org/10.1016/j.medengphy.2005.07.004openalex-snapshot
Analysis of EEG background activity in Alzheimer's disease patients with Lempel–Ziv complexity and central tendency measure
inferredcites →https://doi.org/10.1016/j.neunet.2019.02.005openalex-snapshot
Early Alzheimer’s disease diagnosis based on EEG spectral images using deep learning
inferredcites →https://doi.org/10.1016/j.neurobiolaging.2004.03.008openalex-snapshot
Decreased EEG synchronization in Alzheimer’s disease and mild cognitive impairment
inferredcites →https://doi.org/10.1016/j.neuroimage.2007.09.073openalex-snapshot
Alzheimer's disease diagnosis in individual subjects using structural MR images: Validation studies
inferredcites →https://doi.org/10.1016/j.nicl.2019.102046openalex-snapshot
EEG time signature in Alzheimer´s disease: Functional brain networks falling apart
inferredcites →https://doi.org/10.1016/s0013-4694(97)00079-5openalex-snapshot
Non-linear dynamical analysis of the EEG in Alzheimer's disease with optimal embedding dimension
inferredcites →https://doi.org/10.1016/s0167-8760(03)00118-1openalex-snapshot
Memory-related EEG power and coherence reductions in mild Alzheimer's disease
inferredcites →https://doi.org/10.1016/s0887-6177(03)00039-8openalex-snapshot
Trail Making Test A and B: Normative data stratified by age and education
inferredcites →https://doi.org/10.1016/s0987-7053(01)00254-4openalex-snapshot
Diagnostic value of quantitative EEG in Alzheimer’s disease
inferredcites →https://doi.org/10.1016/s1388-2457(00)00454-5openalex-snapshot
Discrimination of Alzheimer's disease and mild cognitive impairment by equivalent EEG sources: a cross-sectional and longitudinal study
inferredcites →https://doi.org/10.1016/s1388-2457(01)00513-2openalex-snapshot
Mutual information analysis of the EEG in patients with Alzheimer's disease
inferredcites →https://doi.org/10.1016/s1388-2457(01)00579-xopenalex-snapshot
Recurrent neural network-based approach for early recognition of Alzheimer's disease in EEG
inferredcites →https://doi.org/10.1016/s1474-4422(14)70090-0openalex-snapshot
Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria
inferredcites →https://doi.org/10.1016/s1474-4422(16)00062-4openalex-snapshot
Defeating Alzheimer's disease and other dementias: a priority for European science and society
inferredcites →https://doi.org/10.1016/s1474-4422(17)30044-3openalex-snapshot
Epileptic activity in Alzheimer's disease: causes and clinical relevance
inferredcites →https://doi.org/10.1038/nature08538openalex-snapshot
Multimodal techniques for diagnosis and prognosis of Alzheimer's disease
inferredcites →https://doi.org/10.1038/s41598-020-74790-7openalex-snapshot
EEG microstate complexity for aiding early diagnosis of Alzheimer’s disease
inferredcites →https://doi.org/10.1038/srep37685openalex-snapshot
Alpha band disruption in the AD-continuum starts in the Subjective Cognitive Decline stage: a MEG study
inferredcites →https://doi.org/10.1080/01688638808402795openalex-snapshot
Cerebral metabolic effects of a verbal fluency test: A PET scan study
inferredcites →https://doi.org/10.1080/13854049108403297openalex-snapshot
The hopkins verbal learning test: Development of a new memory test with six equivalent forms
inferredcites →https://doi.org/10.1088/0967-3334/27/3/003openalex-snapshot
Entropy analysis of the EEG background activity in Alzheimer's disease patients
inferredcites →https://doi.org/10.1088/1741-2552/ac05d8openalex-snapshot
Deep learning of resting-state electroencephalogram signals for three-class classification of Alzheimer’s disease, mild cognitive impairment and healthy ageing
inferredcites →https://doi.org/10.1093/biomet/54.1-2.167openalex-snapshot
Estimation of the Probability of an Event as a Function of Several Independent Variables
inferredcites →https://doi.org/10.1093/geronj/47.3.p154openalex-snapshot
Boston Naming Test: Shortened Versions for Use in Alzheimer's Disease
inferredcites →https://doi.org/10.1093/geront/9.3_part_1.179openalex-snapshot
Assessment of Older People: Self-Maintaining and Instrumental Activities of Daily Living
inferredcites →https://doi.org/10.1109/icpr.2010.626openalex-snapshot
Boosting Alzheimer Disease Diagnosis Using PET Images
inferredcites →https://doi.org/10.1109/tc.1979.1675255openalex-snapshot
5th International Conference on Pattern Recognition
inferredcites →https://doi.org/10.1109/tnsre.2019.2909100openalex-snapshot
A Dementia Classification Framework Using Frequency and Time-Frequency Features Based on EEG Signals
inferredcites →https://doi.org/10.1111/j.1365-2796.2004.01388.xopenalex-snapshot
Mild cognitive impairment as a diagnostic entity
inferredcites →https://doi.org/10.1111/j.1469-8986.2010.01061.xopenalex-snapshot
ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features
inferredcites →https://doi.org/10.1111/jgs.13820openalex-snapshot
The Montreal Cognitive Assessment—Basic: A Screening Tool for Mild Cognitive Impairment in Illiterate and Low‐Educated Elderly Adults
inferredcites →https://doi.org/10.1126/science.1194144openalex-snapshot
Prediction of Individual Brain Maturity Using fMRI
inferredcites →https://doi.org/10.1136/bmj.m441openalex-snapshot
Calculating the sample size required for developing a clinical prediction model
inferredcites →https://doi.org/10.1142/s0218348x07003691openalex-snapshot
MULTISCALE ENTROPY ANALYSIS OF EEG FROM PATIENTS UNDER DIFFERENT PATHOLOGICAL CONDITIONS
inferredcites →https://doi.org/10.1142/s0219635206001021openalex-snapshot
EEG MARKERS FOR COGNITIVE DECLINE IN ELDERLY SUBJECTS WITH SUBJECTIVE MEMORY COMPLAINTS
inferredcites →https://doi.org/10.1145/2939672openalex-snapshot
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
inferredcites →https://doi.org/10.1155/2011/156869openalex-snapshot
FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data
inferredcites →https://doi.org/10.1155/2014/523216openalex-snapshot
Cortical Source Multivariate EEG Synchronization Analysis on Amnestic Mild Cognitive Impairment in Type 2 Diabetes
inferredcites →https://doi.org/10.1155/2018/5174815openalex-snapshot
Systematic Review on Resting-State EEG for Alzheimer’s Disease Diagnosis and Progression Assessment
inferredcites →https://doi.org/10.1159/000096287openalex-snapshot
Revised Criteria for Mild Cognitive Impairment: Validation within a Longitudinal Population Study
inferredcites →https://doi.org/10.1212/wnl.41.12.1886openalex-snapshot
Prevalence of Alzheimer's disease and other dementias in an elderly urban population
inferredcites →https://doi.org/10.1212/wnl.43.11.2412-aopenalex-snapshot
The Clinical Dementia Rating (CDR)
inferredcites →https://doi.org/10.1214/aos/1013203451openalex-snapshot
Greedy function approximation: A gradient boosting machine.
inferredcites →https://doi.org/10.1214/aos/1176346392openalex-snapshot
A Proof of the Conjecture that the Tukey-Kramer Multiple Comparisons Procedure is Conservative
inferredcites →https://doi.org/10.1371/journal.pone.0018850openalex-snapshot
Multiplexed Immunoassay Panel Identifies Novel CSF Biomarkers for Alzheimer's Disease Diagnosis and Prognosis
inferredcites →https://doi.org/10.21037/qims-21-430openalex-snapshot
Fully automated discrimination of Alzheimer’s disease using resting-state electroencephalography signals
inferredcites →https://doi.org/10.21037/qims.2020.02.08openalex-snapshot
Quantitative magnetic susceptibility assessed by 7T magnetic resonance imaging in Alzheimer’s disease caused by streptozotocin administration
inferredcites →https://doi.org/10.2174/156720510792231720openalex-snapshot
Diagnosis of Alzheimers Disease from EEG Signals: Where Are We Standing?
inferredcites →https://doi.org/10.2174/1567210204558652050openalex-snapshot
Diagnosis of Alzheimer's Disease from EEG Signals: Where Are We Standing?
inferredcites →https://doi.org/10.3389/fninf.2019.00073openalex-snapshot
Analysis of Decision-Making Process Using Methods of Quantitative Electroencephalography and Machine Learning Tools
inferredcites →https://doi.org/10.3390/brainsci9040081openalex-snapshot
EEG Window Length Evaluation for the Detection of Alzheimer’s Disease over Different Brain Regions
inferredcites →https://doi.org/10.4061/2011/539621openalex-snapshot
Slowing and Loss of Complexity in Alzheimer′s EEG: Two Sides of the Same Coin?

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.6445818openalex-extracted
An Explainable Cascading Machine Learning Framework for the Multimodal Characterisation of Mild Cognitive Impairment and Dementia Due to Alzheimer’s Disease
inferred← citeshttps://doi.org/10.1007/978-981-96-4008-9_17openalex-snapshot
Classification of Alzheimer’s Disease from EEG Signals Using Ensemble Learning and Deep Learning Approaches
inferred← citeshttps://doi.org/10.1007/s00429-025-03012-5openalex-snapshot
The neurophysiology of healthy and pathological aging: a comprehensive systematic review
inferred← citeshttps://doi.org/10.1007/s00521-025-11702-8openalex-snapshot
Federated GAN based framework for Alzheimer disease classification using finite impulse response filter techniques
inferred← citeshttps://doi.org/10.1007/s11055-024-01687-7openalex-snapshot
EEG Changes in Patients with Alzheimer’s Disease
inferred← citeshttps://doi.org/10.1007/s11571-024-10153-6openalex-snapshot
STEADYNet: Spatiotemporal EEG analysis for dementia detection using convolutional neural network
inferred← citeshttps://doi.org/10.1007/s11571-024-10198-7openalex-snapshot
Optimal time-frequency localized wavelet filters for identification of Alzheimer’s disease from EEG signals
inferred← citeshttps://doi.org/10.1007/s12559-022-10033-3openalex-snapshot
Efficient Deep Neural Networks for Classification of Alzheimer’s Disease and Mild Cognitive Impairment from Scalp EEG Recordings
inferred← citeshttps://doi.org/10.1007/s13246-024-01425-wopenalex-snapshot
LCADNet: a novel light CNN architecture for EEG-based Alzheimer disease detection
inferred← citeshttps://doi.org/10.1016/j.bbe.2025.05.011openalex-snapshot
Integrative and interpretable framework to unveil the neurophysiological fingerprint of Alzheimer’s disease and mild cognitive impairment: A machine learning-SHAP approach
inferred← citeshttps://doi.org/10.1016/j.bspc.2022.104439openalex-snapshot
Automatic detection of Alzheimer’s disease from EEG signals using low-complexity orthogonal wavelet filter banks
inferred← citeshttps://doi.org/10.1016/j.bspc.2024.106244openalex-snapshot
Metaheuristic optimized time–frequency features for enhancing Alzheimer’s disease identification
inferred← citeshttps://doi.org/10.1016/j.bspc.2025.108390openalex-snapshot
Dual-Transformer Cross-Attention Framework for Alzheimer’s disease detection via dPTE-Guided EEG channel selection and multi-modal integration
inferred← citeshttps://doi.org/10.1016/j.bspc.2025.108667openalex-snapshot
Extraction and interpretation of EEG features for diagnosis and severity prediction of Alzheimer’s Disease and Frontotemporal dementia using deep learning
inferred← citeshttps://doi.org/10.1016/j.clinph.2024.11.013openalex-snapshot
Machine learning based on event-related oscillations of working memory differentiates between preclinical Alzheimer’s disease and normal aging
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2022.106418openalex-snapshot
Classification of mild cognitive impairment based on handwriting dynamics and qEEG
inferred← citeshttps://doi.org/10.1016/j.dajour.2023.100336openalex-snapshot
A novel optimal wavelet filter banks for automated diagnosis of Alzheimer’s disease and mild cognitive impairment using Electroencephalogram signals
inferred← citeshttps://doi.org/10.1016/j.knosys.2023.110858openalex-snapshot
Adazd-Net: Automated adaptive and explainable Alzheimer’s disease detection system using EEG signals
inferred← citeshttps://doi.org/10.1016/j.media.2026.104280openalex-snapshot
DIPOG: A dynamic pooling graph neural network with spatial–temporal-frequency awareness for diagnosis of Alzheimer’s disease
inferred← citeshttps://doi.org/10.1016/j.neuint.2024.105718openalex-snapshot
Role of GABAB receptors in cognition and EEG activity in aged APP and PS1 transgenic mice
inferred← citeshttps://doi.org/10.1016/j.neuroimage.2025.121130openalex-snapshot
Screening tools for subjective cognitive decline and mild cognitive impairment based on task-state prefrontal functional connectivity: a functional near-infrared spectroscopy study
inferred← citeshttps://doi.org/10.1016/j.neuroscience.2024.08.017openalex-snapshot
Towards discovery and implementation of neurophysiologic biomarkers of Alzheimer’s disease using entropy methods
inferred← citeshttps://doi.org/10.1016/j.seizure.2025.04.006openalex-snapshot
A diagnosis and prediction algorithm for juvenile myoclonic epilepsy based on clinical and quantitative EEG features
inferred← citeshttps://doi.org/10.1038/s41746-026-02342-wopenalex-snapshot
Wearable EEG devices in the detection of mild cognitive impairment: a systematic review
inferred← citeshttps://doi.org/10.1063/10.0034533openalex-snapshot
A study of connectivity features analysis in brain function network for dementia recognition
inferred← citeshttps://doi.org/10.1080/10447318.2023.2250605openalex-snapshot
VRNPT: A Neuropsychological Test Tool for Diagnosing Mild Cognitive Impairment Using Virtual Reality and EEG Signals
inferred← citeshttps://doi.org/10.1088/1741-2552/acb96eopenalex-snapshot
An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG
inferred← citeshttps://doi.org/10.1093/brain/awag206openalex-snapshot
The entropic brain today
inferred← citeshttps://doi.org/10.1101/2023.10.11.23296890openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2023.3294618openalex-snapshot
DICE-Net: A Novel Convolution-Transformer Architecture for Alzheimer Detection in EEG Signals
inferred← citeshttps://doi.org/10.1109/bci65088.2025.10931557openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/eiceeai60672.2023.10590088openalex-snapshot
EEG Signal-Based Machine Learning Approaches for Alzheimer's Disease: A Review of Methodological Analysis
inferred← citeshttps://doi.org/10.1109/eiceeai60672.2023.10590201openalex-snapshot
A Novel EEG-Based Deep Approach for Diagnosing Alzheimer's Disease Using Attention-Time-Aware LSTM
inferred← citeshttps://doi.org/10.1109/embc40787.2023.10340854openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icacrs62842.2024.10841571openalex-snapshot
Hybrid Deep Learning and Ensemble Methods for Alzheimer’s Detection from EEG Signals
inferred← citeshttps://doi.org/10.1109/icassp55912.2026.11461987openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/jiot.2025.3525654openalex-snapshot
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inferred← citeshttps://doi.org/10.1111/exsy.13016openalex-snapshot
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inferred← citeshttps://doi.org/10.1111/nyas.70349openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3779215openalex-snapshot
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inferred← citeshttps://doi.org/10.1186/s12880-024-01250-3openalex-snapshot
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inferred← citeshttps://doi.org/10.12677/ap.2025.159535openalex-snapshot
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inferred← citeshttps://doi.org/10.12677/ns.2024.136110openalex-snapshot
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inferred← citeshttps://doi.org/10.17116/jnevro202412404272openalex-snapshot
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inferred← citeshttps://doi.org/10.18517/ijaseit.13.2.18252openalex-snapshot
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inferred← citeshttps://doi.org/10.2139/ssrn.5155795openalex-snapshot
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inferred← citeshttps://doi.org/10.2139/ssrn.5188165openalex-snapshot
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inferred← citeshttps://doi.org/10.3233/jad-230525openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fnagi.2022.884741openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fnagi.2022.888577openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fnagi.2022.988540openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fnagi.2024.1468246openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fnagi.2024.1470836openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fnagi.2025.1496235openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fnagi.2025.1686628openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fnagi.2025.1719981openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fnagi.2026.1900857openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fpsyt.2026.1819726openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/bios15060374openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/diagnostics15111441openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/eng5030078openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/j9030025openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/s26175489openalex-snapshot
From Single-Modal to Multi-Modal Artificial Intelligence in Alzheimer’s Disease: A Systematic Review of Databases, Modalities, Diagnostic Performance, and Clinical Translation Challenges
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