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Automated analysis of facial emotions in subjects with cognitive impairment

PloS one, 2022-01, Vol.17 (1), p.e0262527-e0262527

2022

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Deep Convolutional Neural Networks and Transfer Learning for Measuring Cognitive Impairment Using Eye-Tracking in a Distributed Tablet-Based Environment

IEEE transactions on biomedical engineering, 2021-01, Vol.68 (1), p.11-18

2021

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Disentangling Visual Exploration Differences in Cognitive Impairment

IEEE transactions on biomedical engineering, 2024-04, Vol.71 (4), p.1197-1208

2024

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VisMET: A Passive, Efficient, and Sensitive Assessment of Visuospatial Memory in Healthy Aging, Mild Cognitive Impairment, and Alzheimer's Disease

Learning & memory (Cold Spring Harbor, N.Y.), 2019-03, Vol.26 (3), p.93-100

2019

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A feasibility trial of gamma sensory flicker for patients with prodromal Alzheimer's disease

Alzheimer's & dementia : translational research & clinical interventions, 2021, Vol.7 (1), p.e12178-n/a

2021

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Detecting cognitive impairment by eye movement analysis using automatic classification algorithms

Journal of neuroscience methods, 2011-09, Vol.201 (1), p.196-203

2011

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Eye tracking during a visual paired comparison task as a predictor of early dementia

American journal of Alzheimer's disease and other dementias, 2009-06, Vol.24 (3), p.258-266

2009

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Informed Consent in Two Alzheimer's Disease Research Centers: Insights From Research Coordinators

AJOB empirical bioethics, 2020-04, Vol.11 (2), p.114-124

2020

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An analysis of the study participant and study coordinator experience utilizing an electronic consent (eConsent) in REDCap

Alzheimer's & dementia, 2021-12, Vol.17 (S10), p.n/a

2021

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Equity and Engagement for Neurologic Research Participation at the Goizueta Alzheimer’s Disease Research Center of Emory University

Alzheimer's & dementia, 2022-12, Vol.18 (S11), p.n/a

2022

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A qualitative analysis of study participant and study partner experiences with the consent process: Assessments guiding the development of an electronic consent (ECONSENT): Dementia care research (research projects; nonpharmacological) / Use of technologies

Alzheimer's & dementia, 2020-12, Vol.16 (S7)

2020

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A qualitative analysis of study participant and study partner experiences with the consent process: Assessments guiding the development of an electronic consent (ECONSENT)

Alzheimer's & dementia, 2020-12, Vol.16, p.n/a

2020

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P3‐504: A QUALITATIVE ANALYSIS OF COORDINATOR PERCEPTIONS OF THE CONSENT PROCESS: LESSONS GUIDING THE DEVELOPMENT OF AN ELECTRONIC CONSENT PLATFORM

Alzheimer's & dementia, 2019-07, Vol.15 (7S_Part_22), p.P1162-P1162

2019

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A QUALITATIVE ANALYSIS OF COORDINATOR PERCEPTIONS OF THE CONSENT PROCESS: LESSONS GUIDING THE DEVELOPMENT OF AN ELECTRONIC CONSENT PLATFORM

Alzheimer's & dementia, 2019-07, Vol.15 (7), p.P1162-P1162

2019

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O4‐11‐05: A PROOF OF CONCEPT PHASE II STUDY REPURPOSING ATOMOXETINE FOR NEUROPROTECTION IN MILD COGNITIVE IMPAIRMENT: EVIDENCE FOR TARGET ENGAGEMENT, REGULATION OF CSF BIOMARKERS, AND DISEASE‐MODIFYING POTENTIAL

Alzheimer's & dementia, 2019-07, Vol.15 (7S_Part_24), p.P1263-P1264

2019

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A PROOF OF CONCEPT PHASE II STUDY REPURPOSING ATOMOXETINE FOR NEUROPROTECTION IN MILD COGNITIVE IMPAIRMENT: EVIDENCE FOR TARGET ENGAGEMENT, REGULATION OF CSF BIOMARKERS, AND DISEASE-MODIFYING POTENTIAL

Alzheimer's & dementia, 2019-07, Vol.15 (7), p.P1263-P1264

2019

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P2–287: Characterizing eye movement as a predictor of cognitive decline: Applying machine learning to improve prediction accuracy

Alzheimer's & dementia, 2013-07, Vol.9 (4S_Part_11), p.P462-P463

2013

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Characterizing eye movement as a predictor of cognitive decline: Applying machine learning to improve prediction accuracy

Alzheimer's & dementia, 2013-07, Vol.9 (4), p.P462-P463

2013

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DEVELOPING AN ELECTRONIC CONSENT FOR ADRC

Alzheimer's & dementia, 2019-07, Vol.15 (7), p.P152-P152

2019

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TD‐03‐03: DEVELOPING AN ELECTRONIC CONSENT FOR ADRC

Alzheimer's & dementia, 2019-07, Vol.15 (7S_Part_3), p.P152-P152

2019

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Behavioral performance as a predictor of cognitive decline: Detecting the transition from healthy aging to mild cognitive impairment

Alzheimer's & dementia, 2013, Vol.8 (4), p.S791-S791

2013

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Automated analysis of facial emotions in subjects with cognitive impairment

Deep Convolutional Neural Networks and Transfer Learning for Measuring Cognitive Impairment Using Eye-Tracking in a Distributed Tablet-Based Environment

Disentangling Visual Exploration Differences in Cognitive Impairment

VisMET: A Passive, Efficient, and Sensitive Assessment of Visuospatial Memory in Healthy Aging, Mild Cognitive Impairment, and Alzheimer's Disease

A feasibility trial of gamma sensory flicker for patients with prodromal Alzheimer's disease

Detecting cognitive impairment by eye movement analysis using automatic classification algorithms

Eye tracking during a visual paired comparison task as a predictor of early dementia

Informed Consent in Two Alzheimer's Disease Research Centers: Insights From Research Coordinators

An analysis of the study participant and study coordinator experience utilizing an electronic consent (eConsent) in REDCap

Equity and Engagement for Neurologic Research Participation at the Goizueta Alzheimer’s Disease Research Center of Emory University

Relationships of Cognitive Measures with Cerebrospinal Fluid but Not Imaging Biomarkers of Alzheimer Disease Vary between Black and White Individuals

A qualitative analysis of study participant and study partner experiences with the consent process: Assessments guiding the development of an electronic consent (ECONSENT): Dementia care research (research projects; nonpharmacological) / Use of technologies

A qualitative analysis of study participant and study partner experiences with the consent process: Assessments guiding the development of an electronic consent (ECONSENT)

Differential A/T/N Networks of Cerebrospinal Fluid and Neuroimaging Biomarkers and their Prediction of Cognition between Self‐reported Black/African American and Non‐Hispanic White Individuals

Differential A/T/N Networks of Cerebrospinal Fluid and Neuroimaging Biomarkers and their Prediction of Cognition between Self‐reported Black/African American and Non‐Hispanic White Individuals

P3‐504: A QUALITATIVE ANALYSIS OF COORDINATOR PERCEPTIONS OF THE CONSENT PROCESS: LESSONS GUIDING THE DEVELOPMENT OF AN ELECTRONIC CONSENT PLATFORM

A QUALITATIVE ANALYSIS OF COORDINATOR PERCEPTIONS OF THE CONSENT PROCESS: LESSONS GUIDING THE DEVELOPMENT OF AN ELECTRONIC CONSENT PLATFORM

SORTOUT‐AB: A Study of Race to Understand Alzheimer Biomarkers

O4‐11‐05: A PROOF OF CONCEPT PHASE II STUDY REPURPOSING ATOMOXETINE FOR NEUROPROTECTION IN MILD COGNITIVE IMPAIRMENT: EVIDENCE FOR TARGET ENGAGEMENT, REGULATION OF CSF BIOMARKERS, AND DISEASE‐MODIFYING POTENTIAL

A PROOF OF CONCEPT PHASE II STUDY REPURPOSING ATOMOXETINE FOR NEUROPROTECTION IN MILD COGNITIVE IMPAIRMENT: EVIDENCE FOR TARGET ENGAGEMENT, REGULATION OF CSF BIOMARKERS, AND DISEASE-MODIFYING POTENTIAL

P2–287: Characterizing eye movement as a predictor of cognitive decline: Applying machine learning to improve prediction accuracy

Characterizing eye movement as a predictor of cognitive decline: Applying machine learning to improve prediction accuracy

DEVELOPING AN ELECTRONIC CONSENT FOR ADRC

TD‐03‐03: DEVELOPING AN ELECTRONIC CONSENT FOR ADRC

Behavioral performance as a predictor of cognitive decline: Detecting the transition from healthy aging to mild cognitive impairment

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