Paper Citation Record · LEDGER

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification

As of 15 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2411.17717.

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pith.paper-citation-record.v1
2411.17717 v1

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Outbound references

Observation bebb84ad-ae9c-4fe2-aaf0-a946afa2b92e · outbound

This paper cites Demencia.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Demencia

Reference 1

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This paper cites World Alzheimer Report 2022 | Alzheimer’s Disease International (ADI).

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification World Alzheimer Report 2022 | Alzheimer’s Disease International (ADI)

Reference 2

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This paper cites The precursor of Alzheimer’s disease amyloid A4 protein resembles a cell- surface receptor,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification The precursor of Alzheimer’s disease amyloid A4 protein resembles a cell- surface receptor,

Reference 3

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This paper cites Early diagnosis and treatment of Alzheimer’s disease: new definitions and challenges,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Early diagnosis and treatment of Alzheimer’s disease: new definitions and challenges,

Reference 4

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This paper cites Neural biomarker diagnosis and prediction to mild cognitive impairment and Alzheimer’s disease using EEG technology,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Neural biomarker diagnosis and prediction to mild cognitive impairment and Alzheimer’s disease using EEG technology,

Reference 5

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This paper cites Quantitative EEG analysis disease during resting and memory task in carriers and non-carriers of PS-1 E280A mutation of familial Alzheimer’s,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Quantitative EEG analysis disease during resting and memory task in carriers and non-carriers of PS-1 E280A mutation of familial Alzheimer’s,

Reference 6

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This paper cites Large-scale collaboration in ENIGMA-EEG: A perspective on the meta- analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Large-scale collaboration in ENIGMA-EEG: A perspective on the meta- analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity,

Reference 7

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This paper cites A pipeline for large- scale assessments of dementia EEG connectivity across multicentric settings,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification A pipeline for large- scale assessments of dementia EEG connectivity across multicentric settings,

Reference 8

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This paper cites Multi-feature computational framework for combined signatures of dementia in underrepresented settings,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Multi-feature computational framework for combined signatures of dementia in underrepresented settings,

Reference 9

Resolution: verified exact; doi, observed 2026-08-12T16:50:22.097434Z

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This paper cites EEG-IP: an international infant EEG data integration platform for the study of risk and resilience in autism and related conditions,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification EEG-IP: an international infant EEG data integration platform for the study of risk and resilience in autism and related conditions,

Reference 10

Resolution: verified exact; doi, observed 2026-08-12T16:50:22.080918Z

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This paper cites The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments,

Reference 11

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This paper cites Independent Component Analysis </br> Independent Component Analysis: Principles and Practice,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Independent Component Analysis </br> Independent Component Analysis: Principles and Practice,

Reference 12

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This paper cites Data Archive for the BRAIN Initiative (DABI),.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Data Archive for the BRAIN Initiative (DABI),

Reference 13

Resolution: verified exact; doi, observed 2026-08-12T16:50:22.057798Z

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This paper cites Harmonized multi-metric and multi-centric assessment of EEG source space connectivity for dementia characterization,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Harmonized multi-metric and multi-centric assessment of EEG source space connectivity for dementia characterization,

Reference 14

Resolution: verified exact; doi, observed 2026-08-12T16:50:22.044414Z

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This paper cites The central role of the propensity score in observational studies for causal effects,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification The central role of the propensity score in observational studies for causal effects,

Reference 15

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This paper cites Validation of EEG Pre- processing Pipeline by Test-Retest Reliability,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Validation of EEG Pre- processing Pipeline by Test-Retest Reliability,

Reference 16

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This paper cites Reproducible Neuronal Components found using Group Independent Component Analysis in Resting State Electroencephalographic Data,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Reproducible Neuronal Components found using Group Independent Component Analysis in Resting State Electroencephalographic Data,

Reference 17

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Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification A review of multitaper spectral analysis,

Reference 18

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This paper cites itertools — Functions creating iterators for efficient looping — Python 3.12.6 documentation.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification itertools — Functions creating iterators for efficient looping — Python 3.12.6 documentation

Reference 19

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Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification coherence — SciPy v1.14.1 Manual

Reference 20

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This paper cites EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer’s disease,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer’s disease,

Reference 21

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This paper cites HERMES: Towards an integrated toolbox to characterize functional and effective brain connectivity,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification HERMES: Towards an integrated toolbox to characterize functional and effective brain connectivity,

Reference 22

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This paper cites Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan,

Reference 23

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This paper cites Validation of cross-sectional and longitudinal ComBat harmonization methods for magnetic resonance imaging data on a travelling subject cohort,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Validation of cross-sectional and longitudinal ComBat harmonization methods for magnetic resonance imaging data on a travelling subject cohort,

Reference 24

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Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Tackling EEG Test-Retest Reliability with a Pre-Processing Pipeline Based on ICA and Wavelet-ICA

Reference 25

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Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Electroencephalography Signal Processing: A Comprehensive Review and Analysis of Methods and Techniques,

Reference 26

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This paper cites A deep learning model for the detection of various dementia and MCI pathologies based on resting-state electroencephalography data: A retrospective multicentre study,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification A deep learning model for the detection of various dementia and MCI pathologies based on resting-state electroencephalography data: A retrospective multicentre study,

Reference 27

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Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Alzheimer’s disease,

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This paper cites A novel method for diagnosing Alzheimer’s disease using deep pyramid CNN based on EEG signals,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification A novel method for diagnosing Alzheimer’s disease using deep pyramid CNN based on EEG signals,

Reference 29

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This paper cites Electroencephalography-based classification of Alzheimer’s disease spectrum during computer-based cognitive testing,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Electroencephalography-based classification of Alzheimer’s disease spectrum during computer-based cognitive testing,

Reference 30

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This paper cites Resting state EEG biomarkers of cognitive decline associated with Alzheimer’s disease and mild cognitive impairment,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Resting state EEG biomarkers of cognitive decline associated with Alzheimer’s disease and mild cognitive impairment,

Reference 31

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This paper cites Automatic Classification of Subjects of the PSEN1-E280A Family at Risk of Developing Alzheimer’s Disease Using Machine Learning and Resting State Electroencephalography,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Automatic Classification of Subjects of the PSEN1-E280A Family at Risk of Developing Alzheimer’s Disease Using Machine Learning and Resting State Electroencephalography,

Reference 32

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Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Neural Networks to Recognize Patterns in Topographic Images of Cortical Electrical Activity of Patients with Neurological Diseases,

Reference 33

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Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification EEG functional connectivity and deep learning for automatic diagnosis of brain disorders: Alzheimer’s disease and schizophrenia,

Reference 34

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This paper cites An integrative approach for the analysis of risk and health across the life course: challenges, innovations, and opportunities for life course research,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification An integrative approach for the analysis of risk and health across the life course: challenges, innovations, and opportunities for life course research,

Reference 35

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This paper cites Dementia ConnEEGtome: Towards multicentric harmonization of EEG connectivity in neurodegeneration,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Dementia ConnEEGtome: Towards multicentric harmonization of EEG connectivity in neurodegeneration,

Reference 36

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This paper cites Improving generalizability and study design of Alzheimer’s disease cohort studies in the United States by including under-represented populations,.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Improving generalizability and study design of Alzheimer’s disease cohort studies in the United States by including under-represented populations,

Reference 37

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This paper cites Available: https://www.alzint.org/resource/world-alzheimer-report-2022/.

Comprehensive Methodology for Sample Augmentation in EEG Biomarker Studies for Alzheimers Risk Classification Available: https://www.alzint.org/resource/world-alzheimer-report-2022/

Reference 2024

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Pith citing papers

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