Research graph
References from Electroencephalography in Subjective Cognitive Decline and Mild Cognitive Impairment: Systematic Review of Biomarkers, Classification, and Prognostic Evidence. Local targets link to admitted publications; unresolved targets remain external evidence.
The diagnosis of mild cognitive impairment 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.2011.03.008 · External reference
The characterisation of subjective cognitive decline
10.1016/s1474-4422(19)30368-0 · External reference
Mild cognitive impairment: a concept in evolution
10.1111/joim.12190 · External reference
Mild cognitive impairment that does not progress to dementia: a population-based study
10.1111/jgs.15642 · External reference
Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019
10.1016/s2468-2667(21)00249-8 · External reference
Chinese expert consensus on assessment of cognitive impairment in the elderly
10.1002/agm2.12222 · External reference
Dementia prevention, intervention, and care: 2024 report of the Lancet Standing Commission
10.1016/s0140-6736(24)01296-0 · External reference
Lecanemab in early Alzheimer’s disease
10.1056/nejmoa2212948 · External reference
Lecanemab: appropriate use recommendations
10.14283/jpad.2023.30 · External reference
The affordability of lecanemab, an amyloid-targeting therapy for Alzheimer’s disease: an EADC-EC viewpoint
10.1016/j.lanepe.2023.100657 · External reference
Culture-fair cognitive screening tools for assessment of cognitive impairment: a systematic review
10.3233/adr-230194 · External reference
Developing guidelines for the translation and cultural adaptation of the Montreal Cognitive Assessment: scoping review and qualitative synthesis
10.1192/bjo.2021.1067 · External reference
Revised criteria for diagnosis and staging of Alzheimer’s disease: Alzheimer’s Association Workgroup
10.1002/alz.13859 · External reference
Clinical diagnosis of Alzheimer’s disease: recommendations of the International Working Group
10.1016/s1474-4422(21)00066-1 · External reference
EEG biomarkers in Alzheimer’s and prodromal Alzheimer’s: a comprehensive analysis of spectral and connectivity features
10.1186/s13195-024-01582-w · External reference
EEG frequency bands in subjective cognitive decline: a systematic review of resting state studies
10.1016/j.biopsycho.2024.108823 · External reference
Neural decoding of EEG signals with machine learning: a systematic review
10.3390/brainsci11111525 · External reference
Assessing the potential of EEG in early detection of Alzheimer’s disease: a systematic comprehensive review (2000-2023)
10.3233/adr-230159 · External reference
A systematic review of cognitive event-related potentials in mild cognitive impairment and Alzheimer’s disease
10.1016/j.bbr.2020.112904 · External reference
Functional and effective EEG connectivity patterns in Alzheimer’s disease and mild cognitive impairment: a systematic review
10.3389/fnagi.2025.1496235 · External reference
The importance of subjective cognitive decline recognition and the potential of molecular and neurophysiological biomarkers-a systematic review
10.3390/ijms241210158 · External reference
Machine and deep learning trends in EEG-based detection and diagnosis of Alzheimer’s disease: a systematic review
10.3390/eng5030078 · External reference
Deep learning techniques for automated Alzheimer’s and mild cognitive impairment disease using EEG signals: a comprehensive review of the last decade (2013-2024)
10.1016/j.cmpb.2024.108506 · External reference
The PRISMA 2020 statement: an updated guideline for reporting systematic reviews
10.1136/bmj.n71 · External reference
PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods
10.1136/bmj-2024-082505 · External reference
The revised JBI critical appraisal tool for the assessment of risk of bias for analytical cross-sectional studies
10.11124/jbies-24-00523 · External reference
The revised JBI critical appraisal tool for the assessment of risk of bias for cohort studies
10.11124/jbies-24-00103 · External reference
10.46658/jbirm-17-06
10.46658/jbirm-17-06 · External reference
Assessing bias in studies of prognostic factors
10.7326/0003-4819-158-4-201302190-00009 · External reference
GRADE guidance: 31. Assessing the certainty across a body of evidence for comparative test accuracy
10.1016/j.jclinepi.2021.04.001 · External reference
GRADE guidance 37: rating imprecision in a body of evidence on test accuracy
10.1016/j.jclinepi.2023.10.005 · External reference
A novel connectome-based electrophysiological study of subjective cognitive decline related to Alzheimer’s disease by using resting-state high-density EEG EGI GES 300
10.3390/brainsci10060392 · External reference
EEG spectral analysis as a putative early prognostic biomarker in nondemented, amyloid positive subjects
10.1016/j.neurobiolaging.2017.05.017 · External reference
An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG
10.1088/1741-2552/acb96e · External reference
Understanding the role of self-attention in a transformer model for the discrimination of SCD from MCI using resting-state EEG
10.1109/jbhi.2024.3390606 · External reference
PET-validated EEG-machine learning algorithm predicts brain amyloid pathology in pre-dementia Alzheimer’s disease
10.1038/s41598-023-36713-0 · External reference
Exploring network properties across preclinical stages of Alzheimer’s disease using a visual short-term memory and attention task with high-density electroencephalography: a brain-connectome neurophysiological study
10.3233/jad-215421 · External reference
Differentiation of subjective cognitive decline, mild cognitive impairment, and dementia using qEEG/ERP-based cognitive testing and volumetric MRI in an outpatient specialty memory clinic
10.3233/jad-220616 · External reference
Reproducibility of EEG functional connectivity in Alzheimer’s disease
10.1186/s13195-020-00632-3 · External reference
Deep learning of resting-state electroencephalogram signals for three-class classification of Alzheimer’s disease, mild cognitive impairment and healthy ageing
10.1088/1741-2552/ac05d8 · External reference
The power of EEG to predict conversion from mild cognitive impairment and subjective cognitive decline to dementia
10.1159/000508392 · External reference
Eyes-open and eyes-closed EEG of older adults with subjective cognitive impairment versus healthy controls: a frequency principal components analysis study
10.1016/j.brainres.2024.149399 · External reference
Optimizing electrode configurations for EEG mild cognitive impairment detection
10.1038/s41598-024-84277-4 · External reference
Power spectral changes of quantitative EEG in subjective cognitive decline: comparison of community normal control groups
10.2147/ndt.s320130 · External reference
Quantitative EEG spectral and connectivity analysis for cognitive decline in amnestic mild cognitive impairment
10.3233/jad-230485 · External reference
Electroencephalography-based classification of Alzheimer’s disease spectrum during computer-based cognitive testing
10.1038/s41598-024-55656-8 · External reference
Electroencephalography for early detection of Alzheimer’s disease in subjective cognitive decline
10.12779/dnd.2022.21.4.126 · External reference
Neural biomarker diagnosis and prediction to mild cognitive impairment and Alzheimer’s disease using EEG technology
10.1186/s13195-023-01181-1 · External reference
Neurophysiological markers in community-dwelling older adults with mild cognitive impairment: an EEG study
10.1186/s13195-023-01368-6 · External reference
Memorization test and resting state EEG components in mild and subjective cognitive impairment
10.2174/1567205015666180427114520 · External reference
Can a novel high-density EEG approach disentangle the differences of visual event-related potential (N170), elicited by negative facial stimuli, in people with subjective cognitive impairment?
10.3233/jad-180223 · External reference
The STARD-AI reporting guideline for diagnostic accuracy studies using artificial intelligence
10.1038/s41591-025-03953-8 · External reference
Data leakage in deep learning studies of translational EEG
10.3389/fnins.2024.1373515 · External reference
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
10.1136/bmj-2022-070904 · External reference
